Development of capstone project attitude scales

Development of capstone project attitude scales
Rex P. Bringula
Published online: 13 December 2013
# Springer Science+Business Media New York 2013
Abstract This study attempted to develop valid and reliable Capstone Project Attitude
Scales (CPAS). Among the scales reviewed, the Modified Fennema-Shermann Mathematics
Attitude Scales was adapted in the construction of the CPAS. Usefulness,
Confidence, and Gender View were the three subscales of the CPAS. Four hundred
sixty-three students answered the questionnaire. The validity of the scales was ensured
through pilot testing and factor analysis with a threshold value of at least 0.50.
Meanwhile, the reliability of the items was determined through Cronbach’s alpha
analysis. All items with Cronbach’s alpha value of less than 0.70 were discarded. It
was shown that Usefulness, Confidence, and Gender View had Cronbach’s alpha
values of 0.837, 0.748, and 0.818, respectively. Confirmatory factor analysis (CFA)
was utilized to confirm the model and discriminant validity was used to find out if each
of the constructs was unique in itself. It was also revealed that the measurement model
of the revised scales provided a good fit (CFI=0.97; AGFI=0.94; RMSEA=0.038) and
the constructs were distinct from one another. From the initial draft of the questionnaire
with 47 items, only 15 items were retained. Nonetheless, CPAS was able to capture
more than 50 % (%cumulative variance=57 %) of the attitudes exhibited by the
students in Capstone Project. Implications and directions for future research that could
be derived from this study were also presented.
Keywords Attitudes . Attitude scale . Capstone project . ITeducation
1 Introduction
Attitude is “a covert, unexpressed psychological predisposition or tendency” (Shelley
2006, p. 61) towards a person, an object, or a concept (Haddock and Maio 2007;
Matwin and Fabrigar 2007; Abbas et al. 2011). It can also be an evaluation of places,
events, ideas (Abbas et al. 2011), facts, or states (Ponticell 2006). A person could use
his/her mental positions (cognitive), feelings (affective), or behaviors (behavioral
domain) while evaluating these predispositions or tendencies (Ponticell 2006). A
Educ Inf Technol (2015) 20:485–504
DOI 10.1007/s10639-013-9297-1
R. P. Bringula (*)
College of Computer Studies and Systems, University of the East, Manila, Philippines
e-mail: rex_bringula@yahoo.com
person’s evaluation could either be positive or negative (Matwin and Fabrigar 2007;
Abbas et al. 2011). The attitudes of a person could vary in strength (weak or strong)
(Shelley 2006) and direction (i.e., democratic view or dictatorship view). Nevertheless,
attitudes can simply be defined as the expressions of fundamental likes or dislikes
(Shelley 2006).
It is important to study attitudes because they affect both the way we perceive the
world and how we behave (Haddock and Maio 2007). Thus, since the conception of
attitudes in the 1920s (Salinas 2006), they have been the subject of various researches
in the academic fields. For example, Mohd and Mahmood (2011) found out that
attitudes had a significant contribution to mathematical problem solving and mathematics
achievement. More specifically, the study of Coetzee and Van derMerwe (2010)
revealed that even though students perceived statistics to be technical, complicated, and
difficult, they were interested in studying it and they believed that statistics was an
important subject. They also showed that there was a relationship between the students’
perceived competence in mathematics and the degree to which they felt confident to
master statistics. Furthermore, attitudes, such as liking (or disliking) mathematics,
showing difficulty in doing mathematics, as well as placing importance on luck and
talent in doing mathematics, were found to have a negative influence on mathematics
achievement while educational expectations positively influenced mathematics
achievement (Ramirez 2005).
In science, expected achievement and attitudes toward science were shown to be
strongly related (Craker 2006). This was also confirmed in the studies of Mettas et al.
(2006), and Nasr and Soltani (2011). Students who enjoyed learning science had higher
achievement in science (Mettas et al. 2006; Nasr and Soltani 2011). On the other hand,
students who associated luck and lots of natural talent in order to do well in science tended
to show lower achievement test scores in science (Mettas et al. 2006). Interestingly,
students who were good in science and mathematics weremore positive about their ability
to use technology as compared to their social science counterparts (Kahveci 2010).
In a sample of elementary and middle school students, it was disclosed that attitudes
towards reading were positively related to achievement in reading (Petscher 2010).
Behavioral attitudes, such as authoritative parenting styles, were also found to be
associated with higher levels of children’s school achievement (Kordi and Baharudin
2010). Recently, Bringula et al. (2012) revealed that the attitude of not being confident
towards programming was more likely to predict all types of programming errors.
Gender view on mathematics and science was also investigated in different studies.
Meece et al. (2006) reviewed different theories on motivation (e.g., attribution,
expectancy-value, self-efficacy, and achievement goal perspectives) and found out that
boys reported stronger ability, interest, and beliefs in mathematics and science, whereas
girls had more confidence and interest in language arts and writing. LaLonde et al.
(2003), and Brandell and Staberg (2008) supported this finding as they revealed that
boys had the strongest beliefs in mathematics as a male domain. Cracker (2006) also
reported that females tended to view science as a male domain. These findings indicate
that stereotyping exists in the mathematics and science courses.
Despite the rich and still growing body of literature on attitudes, there are still no
studies conducted to determine the attitudes of computing students towards Capstone
Project. This gap is partially attributed to the absence of valid and reliable scales to
measure the students’ attitudes towards Capstone Project. Thus, this study has been
486 Educ Inf Technol (2015) 20:485–504
conceived. The main objective of this study was to develop valid and reliable scales to
measure the attitudes of students towards Capstone Project. In effect, the outputs could
further be utilized in future studies. Specifically, it aims 1) to construct valid and
reliable attitudinal scales on Capstone Project through factor analysis, and 2) to develop
a good fit model of the developed scales using confirmatory factor analysis.
2 Literature review
2.1 Capstone project
Lunt et al. (2008, p. 58) suggested that one of the principles of curriculum design for
undergraduate degree programs in Information Technology is that “the curriculum must
provide students with a capstone experience that gives them a chance to apply their
skills and knowledge to solve a challenging problem.” This principle could be in
response to the demand of the industry to hire graduates who were technically
competent, with strong communication skills, good leadership and team player qualities,
and strong work ethic (Russell et al. 2005). In order to meet this demand, various
degree programs offered a course called Capstone Project.
In a business degree program, Capstone Project was viewed as a method of evaluating
the overall student-learning outcomes (Payne et al. 2008). Students were given an
opportunity to demonstrate their higher-order cognitive dimensions of learning as well
as the affective and skills-based dimensions of learning (Payne et al. 2008; Moshkovich
2012). Similarly, capstone courses in Psychology and Information Technology Management
(ITM) were designed to prepare students for jobs after graduation (Beer et al.
2011; Brandon et al. 2002). The courses also provided students a learning environment
and opportunity to exercise the skills acquired in schools (Beer et al. 2011).
Meanwhile, the focus of engineering Capstone Projects was on teamwork, demonstration
of communication skills, development of an awareness of professional responsibility,
and design, construction, debugging, etc. of a device or system (Meyer 2005).
This was in line with the engineering students’ outcome proposed by the Accreditation
Board for Engineering and Technology (ABET 2012).
Capstone Project is also part of the curriculum of computing degree programs
(Computer Science (CS), Information Technology (IT), and Information Systems
(IS)). The CS Capstone Project requires the students to apply their technical skills as
well as the knowledge and skills of the liberal arts such as Ethics, Communication,
Psychology, Sociology, and Mathematics (Miles and Kelm 2007). Likewise, the IS
Capstone Project helps students “understand the big picture, i.e. how knowledge
acquired from all the courses in their curriculum converges together and how students
can apply this knowledge to develop an information system” (Kumar et al. 2004, p.
174). In this manner, students would realize the role and relevance of each course
(Hartzel et al. 2003).
Lunt et al. (2008) further stressed that IT Capstone Project has three common
characteristics. These are as follows: 1) students are divided into teams of typically 4
to 8 members each; 2) each team is given a real world project or problem to solve; and
3) this project takes many weeks to complete (typically 14 or more). It is further
explained that IT Capstone Project may be a one-semester or a two-semester course
Educ Inf Technol (2015) 20:485–504 487
which may be taken during the student’s last year of stay in school. Students work in
teams in designing and implementing projects. Cost, safety, efficiency, and suitability
for the intended user are some of the considerations in doing the projects. The projects
may be developed exclusively for class or for on- or off-campus clients. While the
emphasis of the course is on project work and student presentations, intellectual property
rights, copyrights, patents, law, and ethics can also be included in the discussions.
Though different degree programs have different forms of capstone course
(Moshkovich 2012), they follow the same requirements. Different studies have shown
the following requirements for the Capstone Project.
& combination of business and IT issues (Brandon et al. 2002; Hartzel et al. 2003);
& experiential component in the form of a “real-life” project (Brandon et al. 2002);
& advanced conceptual segment in the form of business systems analysis, case
studies, documentation, verbal reporting, and discussion participation (Brandon
et al. 2002; Hartzel et al. 2003); and
& soft skills, including effective interpersonal relationships, self-management strategies,
teamwork, problem solving, etc., and social skills (Brandon et al. 2002;
McGann and Cahill 2005).
2.2 Attitudes scales
Tapia and Marsh (2000) developed the Attitudes Towards Mathematics Inventory
(ATMI). Responses of 545 students under the mathematics secondary curriculum were
examined to determine their attitudes towards mathematics and to find out the underlying
dimensions of the instrument. It was revealed that after dropping nine items from
the original 49 items, the alpha value of the instrument yielded to 0.95. A Likert scale
format (1-strongly disagree, 2-disagree, 3-neutral, 4-agree, and 5-strongly agree) was
used to measure the attitudes of the students. Factor analysis showed that there were
three subscales. The subscales and their alpha values were self-confidence (0.94),
enjoyment of mathematics (0.92), and value of mathematics (0.84). In 2004, Tapia
and Marsh (2004) revised the scale. The revised ATMI had four factors when subjected
to a maximum likelihood factor analysis with a varimax rotation. The factors (alpha
values in parentheses) were self-confidence (0.95), value of mathematics (0.89),
enjoyment of mathematics (0.89), and motivation (0.88).
Asante (2012) utilized the ATMI. A higher score on the ATMI (which had 200 points
maximum) indicated more positive attitudes towards mathematics. Before ATMI was
administered to 109 boys and 72 girls from conveniently sampled three high schools, Asante
(2012) pretested the questionnaire within the Ghanaian culture and yielded a highly reliable
coefficient of 0.94. Thus, the ATMI could be utilized in the Ghanaian culture.
Abbas et al. (2011) adapted the Modified Fennema-Shermann Mathematics Attitude
Scales (MFSMAS). Doepken et al. (2003) developed this questionnaire. In the study of
Abbas et al. (2011), a twenty-eight (28)-item questionnaire was administered to 600
students in seven secondary schools in Model Town and Kahna area of Lahore. The
questionnaire determined the attitudes of the students towards science. However, it was
not reported whether reliability and validity tests were conducted in the adapted questionnaires.
Meanwhile, Yara (2009) utilized the Student Attitude Scale (SAT) which was also
patterned after the MFSMAS. It consisted of 22 items which were made up of 11
488 Educ Inf Technol (2015) 20:485–504
positively worded and 11 negatively worded items to which the 1,542 students responded.
Students’ responses could be from strongly disagree (1) to strongly agree (4). Fifty (50)
students in three (3) different schools answered the pretest of the questionnaire in order to
determine the reliability of the instrument. A Cronbach’s alpha value of 0.82 was obtained
that showed that the instrument was reliable and it could be used for the study. However,
no reports were made to show if the instrument was tested for its validity.
Abdullah and Zakaria (2011) developed the Attitudes Towards Geometry Survey
(ATGS). The study involved 161 students in one of the states in Malaysia. Students
could choose from 1 (strongly disagree), 2 (disagree), 3 (not sure), 4 (agree), and 5
(strongly agree) in answering the ATGS. Item analysis revealed that the three subscales
of ATGS were reliable. Enjoyment (i.e., enjoyment of learning geometry topics),
Valuation (i.e., valuation of geometry), and Motivation (i.e., motivation towards geometry)
were the three subscales of ATGS. Enjoyment, Valuation, and Movation had
Cronbach’s alpha values of 0.85, 0.77, and 0.69, respectively. The Kaiser-Meyer-Olkin
Measure of Sampling Adequacy of 0.825 warranted further use of factor analysis.
Factor analysis revealed that only 17 of the 24 items were valid. Reliability analysis
was not repeated on the 17 retained items.
Mohd and Mahmood (2011) used the Student Attitude Questionnaire. The reliability
of the questionnaire was pretested to 30 students and was found to be highly reliable
(Cronbach’s alpha value=0.720). The questionnaire was subdivided to three factors—
confidence, patience, and willingness towards mathematics problem solving. It was
then administered to 153 students who were composed of 93 diploma and 60 bachelor
students. Respondents could choose from 1 (totally disagree), 2 (disagree), 3 (agree), or
4 (totally agree) as a response to the items. There was no report in the study if validity
tests were conducted in the questionnaire.
Tekerek et al. (2011) utilized a thirty-eight (38) Mathematics Attitude Questionnaire
(MAQ) in order to determine the attitudes of 122 Computer Education and Instructional
Technology undergraduates of four different universities in Turkey. Factor analysis
revealed that likes and interest (factor loading ranging from 0.55 to 0.71), anxiety and
confidence (0.65–0.80), occupational and daily importance (0.48–0.76), and enjoyment
(0.51–0.79) were the four factors of MAQ. The study stated that MAQ was developed
by Duatepe and Cilesiz (1999) but it did not report any modification in the said
questionnaire. Furthermore, Tekerek et al. (2011) did not conduct further test such as
reliability analysis on the items.
In the study of Coetzee and Van der Merwe (2010), a cross-sectional survey design
was used and the SATS-36 (Survey of Attitudes Towards Statistics-36) was administered
to a sample of convenience consisting of 235 students enrolled in Industrial and
Organizational Psychology at a large tertiary institution in South Africa. The SATS-36
used a 7-point Likert scale (1=strongly disagree, 4=neither disagree nor agree, 7=
strongly agree). The six subscales of SATS-36 were the following:
& Affect—students’ feelings concerning statistics; five items, factor loadings (f.l.)=
0.52–0.767; Cronbach’s alpha (α)=0.801;
& Cognitive Competence—students’ attitudes about their intellectual knowledge and
skills when applied to statistics; six items, (f.l.)=0.523–0.728; α = 0.798;
& Value—students’ attitudes about the usefulness, relevance, and worth of statistics in
personal and professional life; eight items, (f.l.)=0.517–0.754; α = 0.828;
Educ Inf Technol (2015) 20:485–504 489
& Difficulty—students’ attitudes about the difficulty of statistics as a subject; five
items, (f.l.)=0.35–0.778; α = 0.662;
& Interest—students’ level of individual interest in statistics; four items; f.l. = 0.663–
0.768; α = 0.827; and
& Effort—amount of work the student spends to learn statistics; three items, f.l. =
0.77–0.927; α = 0.853.
In the study of Orhun (2007), 5th semester students (42 females, 31 males) from the
Mathematics Department of Anadolu University answered the Attitude Towards Mathematics
(ATM) questionnaire. The questionnaire was intended to find out the respondents’
positive and negative feelings towards mathematics. There were 20 items, most
of which were related to classroom settings (e.g., “I am afraid of mathematics exams,”
“I enjoy mathematics classes,” etc.), that could be answered by a five-point scale
(Completely Agree, Agree, Undecided, Disagree, Completely Disagree). No reports
were made on the validity and the reliability of the items.
Lastly, Doepken et al. (2003) developed the Modified Fennema-Sherman Mathematics
Attitude Scales (MFSMAS). Confidence towards mathematics (6 items positive,
6 items negative), Usefulness of the subject (6 items positive, 6 items negative), Subject
perceived as a male domain (6 items positive, 5 items negative), and Perception of the
students on their teacher’s attitudes (6 items positive, 6 items negative) were the four
subscales of the MFSMS. There was a total of 47 items. The responses were similar to
those used in the ATM and ATGS.
3 Development of the instrument
3.1 Research locale
The study was conducted at the College of Computer Studies and Systems (CCSS) of
the University of the East in Manila. CCSS offers 4-year degree programs in Computer
Science and Information Technology. Both degree programs have Capstone Projects.
The distinction between the Capstone Projects for the degrees is depicted in Fig. 1.
As shown in Fig. 1, all students would enroll in Methods of Research for IT
(MERIT). For Bachelor of Science in Computer Science (BSCS) students enrolled in
MERIT, they were expected to come up with a research topic. On the other hand, the
introduction, review of literature and related systems, and methodology sections of the
Fig. 1 Capstone project classifications at the college of computer studies and systems
490 Educ Inf Technol (2015) 20:485–504
manuscript, and proof of systems development agreement between the team and a
target client were the deliverables for students taking up Bachelor of Science in
Information Technology (BSIT). If the students passed MERIT, they would enroll
either in Capstone Planning (CPROP) or ThesisWriting A (ThesA) depending on their
degree programs. In Capstone Planning (CPROP), the whole manuscript and the
software would be the final requirements of the course. Eventually, in Capstone
Development (CPROD), the software would be implemented in the client’s company.
Meanwhile, CS students in ThesA should present the three chapters of the manuscript.
In ThesB (Thesis Writing B), CS students would present the software and the
findings of the study. Also, the final documentation would also be submitted. All of
these courses were on consultation basis, i.e., no teachers were assigned on the subject
and students would ask the help of their thesis advisers.
The final grades of the students were computed based on two components—oral
defense and advisers’ grades.A three-man committeewould evaluate the Capstone Project
of the students. This evaluation constituted 60 % of the students’ final grades. The
advisers’ grades could only be given to the students if they could pass the oral defense.
3.2 Population, sample size, and data-gathering procedure
There were 880 students enrolled in Capstone Project courses during the First Semester
of SY 2011–2012. Thirty-one (31) students who participated in the pilot-testing of the
questionnaire were subtracted from 880. Thus, the actual population considered was
849. Using Sloven’s formula with e=0.05, a sample size of 272 was computed.
The distribution of the questionnaire was made during the First Semester of SY
2011–2012. The first distribution of the survey forms was done during the thesis
orientation which was held at the start of the semester and was convened in a hall with
a 416 seating capacity. Three hundred eighty-six (386) forms, which exceeded the
required computed sample size, were retrieved. To achieve higher confidence in
performing factor and reliability analyses, more data were gathered by distributing
additional 100 survey forms throughout the first semester and retrieving 77 forms. The
total number of usable forms was 463.
3.3 Data analysis
Factor analysis with a threshold value of at least 0.50 was used to determine the validity
of the items on each construct. This factor loading was a very significant factor loading
(Abdullah and Zakaria 2011; Liman et al. 2011; Maleki et al. 2012). This was selected
to achieve more valid constructs. It can also be noted that the factor loading utilized in
this study was higher than the factor loadings utilized by Kahveci (2010), Ozturk
(2011), and Ramaswami and Babo (2012). They used a factor loading of 0.40. Principal
Component Analysis and Varimax Rotation were utilized in extraction and rotation
methods, respectively.
Cronbach’s alpha (α) analysis was utilized to determine the reliability of the items.
Items with Cronbach’s α of less than 0.70 were discarded. This Cronbach’s α was the
most commonly used acceptability threshold of .70 for reliability analysis (Ozturk
2011) and above the 0.60 minimum value (Nunally, 1967 cited in Asante 2012
and in Ozturk 2011).
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Confirmatory factor analysis, with Comparative-Fit Index (CFI), Adjusted
Goodness-of-Index (AGFI), and Root Mean Square Error of Approximation
(RMSEA) fit indices, were employed to assess the good fit of the developed scales.
The model was of good fit if all were satisfied: CFI>= 0.90, AGFI>= 0.90, and
RMSEA<0.07 (Hair et al. 2010; Feldt 2013). Discriminant validity was also
established through comparison of the average variance extracted (AVE) for each
construct with the squared interconstruct correlations associated with the factor.
3.4 Steps in the development of the scale
The following steps served as guides in the development of the scales.
1. Develop the initial draft of the scales.
2. Check the validity of content. If content is vague or not applicable, revise the scale.
3. Check factorial validity of the items. If items are not valid, delete the invalid items
and repeat this step until all items are valid.
4. Check reliability of the items.
a. If items are not reliable, delete the unreliable item and repeat this step until all
items are reliable.
b. Repeat Step 3.
5. If all items are valid and reliable, perform confirmatory factor analysis and check
the discriminant validity of the factors.
6. Develop the final scales.
4 Results
4.1 The respondents
The respondents of the study were composed of 420 IT and 43 CS students. There were
more male (f=296, 64 %) than female (f=167, 36 %) respondents. The composition of
the respondents in terms of course enrolled in is as follows: MERIT (f=302, 65 %),
CPROD (f=115, 25 %), CPROP (f=29), THESA (f=12, 3 %), and THESB (f=5, 1 %).
4.2 Development of the scales
4.2.1 Step 1. Development of the scales
Modified Fennema-Sherman Mathematics Attitude Scale (MFSMAS) served as basis
in the development of the initial draft of the questionnaire. It was chosen among the
attitude scales reviewed because of its unique component—gender view. A genderrelated
issue, such as fewer women being attracted to computing degrees, was raised in
computing literature. With the construction of this attitude scales, attitudes between
men and women in computing could further be investigated.
MFSMAS was revised to fit the context of the study. The original 47-item questionnaire
was reduced into a 36-item questionnaire. The first draft of the 36-item
492 Educ Inf Technol (2015) 20:485–504
attitude scales towards Capstone Project is shown in Table 1. The responses of the
students were also based on the said scales but they had slight modifications. In the
scales, respondents of the study could answer the statements as Strongly disagree (1),
Disagree (2), Undecided/Can’t Tell Right Now (3), Agree (4), or Strongly agree (5).
This study retained all responses except “Undecided/Can’t Tell Right Now.” It was
replaced with Moderately agree. In this manner, the responses would be in a
continuum and they could exhibit an interval scale. Furthermore, an “undecided”
response is quite difficult to interpret. For example, an undecided response in “I am
sure of myself when I enrolled Capstone Project” (See Item 10, Table 1.) was hard to
interpret. Thus, assigning the value 3 to Moderately agree was deemed to be more
appropriate.
4.2.2 Step 2. Content validation
The first draft of the scales was content-validated. There were two parts of content
validation. First, it was pilot-tested to thirty-one (31) students who were enrolled in a
Capstone Project course. They were interviewed to gather their clarifications, suggestions,
and recommendations to improve the questionnaire. The second phase solicited
the opinions, suggestions, and recommendations of two faculty-advisers on how to
improve the questionnaire. These served as inputs in the modification of the first draft.
The reasons for the deletions and revisions of the items are presented.
The question could not be answered by some students Item 1 was deleted because it
was found out to be inapplicable. It can be noted that the Capstone Project at the
College of Computer Studies and Systems involves five courses. The phases of the
students on the capstone project were diverse. The question “I learned a lot in
Capstone Project” would not be appropriate since there were students who were still
in the learning phase on the said courses. Moreover, changing the tense of “learned” to
“will learn” could still not make the question fit since there were students (i.e., CPROD
students) that almost completed the course. Thus, it was decided to delete this question.
Ethical considerations The two faculty-advisers recommended deleting adviser-related
items (Items 2, 12, 23, 34, and 36) due to ethical considerations and irrelevance of the
question. Advisers were expected to execute the highest professional and ethical standards
in dealing with their advisees. As professional advisers, their main task was to oversee the
overall progress of the project. The answer to the question such as, “My adviser has been
interested in our progress in Capstone Project.” (Item 34), would be obvious since this
was what exactly the advisers were doing. Thus, in the context of this study, Items 2, 12,
34, and 36 would be irrelevant and there was no need to ask such question.
Redundancy Items 28 and 32 were deleted because they were redundant with Item 16.
The positive statement, i.e. Item 16, was retained.
Difference in the rating performance of the two subject matters Items 19, 25, and 26
were also found not fit to be retained. This was attributed to the nature of the subject
matter. The MFSMAS asked the perception of the students on the student’s individual
performance. On the other hand, in the Capstone Project, team members were rated as a
Educ Inf Technol (2015) 20:485–504 493
group. In the context of the study, majority of the grades (60 %) of the students were
dependent on the group’s performance. One student also commented on the question “I
can get good grades in Capstone Project.” It was not clear if the grades would refer to
group grades or individual grades. It was decided to delete these items.
Table 1 First draft of the scales
No. Items
1 I learned a lot in Capstone Project.
2 My adviser has been interested in our progress in Capstone Project.
3 Capstone Project will eventually help me earn a living.
4 Capstone Project is important to me in my life’s work.
5 Males are naturally better than females in Capstone Project.
6 Capstone Project is a hard subject for me.
7 Females could be good in Capstone Project.
8 I will need Capstone Project for my future work.
9 When a female has a Capstone Project, she should have a male group mate.
10 I am sure of myself when I enrolled in Capstone Project.
11 I don’t expect to use my subject Capstone Project when I get out of school.
12 I would talk to my adviser about a career where I could apply what I learned in Capstone Project.
13 Women can do just as well as men in Capstone Project.
14 Capstone Project is a worthwhile, necessary subject.
15 I would have more faith in a man than in a woman in solving issues in Capstone Project.
16 I’m not the type to do well in Capstone Project.
17 Taking the Capstone Project subject is a waste of time.
18 Capstone Project is the worst subject.
19 I think I could handle the difficulties in Capstone Project.
20 I will use the subject Capstone Project in many ways as a professional.
21 Females are as good as males in Capstone Project.
22 I see Capstone Project as something I won’t use very often when I get out of college.
23 I feel that my adviser ignores me when I try to settle issues.
24 Women certainly are smart enough to do well in Capstone Project.
25 Most subjects I can handle are okay but I just can’t do a good job with Capstone Project.
26 I can get good grades in Capstone Project.
27 The skills I will learn in Capstone Project are needed for my future work.
28 I know I can do well in Capstone Project.
29 Studying Capstone Project is just as good for women as for men.
30 Doing well in Capstone Project is not important for my future.
31 Capstone Project is not important for my life.
32 I’m not good in Capstone Project.
33 I study Capstone Project because I know how useful it is.
34 My adviser makes me feel I have the ability to go on in Capstone Project.
35 I would trust a female just as much as I would trust a male to solve important issues in Capstone Project.
36 My adviser thinks I’m the kind of person who could do well in Capstone Project.
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Considering these modifications, 25 items were retained. The scales had three
subscales—Usefulness, Confidence, and Gender View. There were 12 items under
Usefulness (U); 4 items under Confidence (C); and 9 items under Gender View (G).
It was decided to add five additional items (Items 26 to 30) for Confidence to balance
the number of items. The second draft of the attitude scales is shown in Table 2.
4.2.3 Step 3. Factorial validity of the items
The second draft of the attitude scales was distributed to the actual respondents. Data
gathered from the respondents were subjected to factor analysis using the Principal
component analysis with Varimax rotation to determine the factorial validity of the
items. The results are shown in Table 3.
As shown in Table 3, the first run of factor analysis revealed that all items on
Usefulness and Gender view were valid (i.e., factor loadings (f.l.) of at least 0.50). On
the other hand, one item (“Capstone Project is a difficult subject”) under Confidence
was not found to be valid since its f.l. < 0.50. Thus, this item was deleted. After it was
deleted, factor analysis was again deployed and the remaining items under the construct
Confidence were all found valid.
The Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) on Usefulness
(KMO=0.898), Confidence (KMO=0.817), and Gender View (KMO=0.849) were all
greater than 0.80 that revealed that these were all meritorious (George and Mallery
2009) or great (Field 2009) values. Furthermore, the Barlett’s Test of Sphericity on
Usefulness (χ2=2,112.598, df=66, p<0.05), Confidence (χ2=748.389, df=28,
p<0.05), and Gender View (χ2=1,158.892, df=36, p<0.05) were all found significant.
4.2.4 Step 4. Reliability of the items
Since the validity of the constructs was established, the test of reliability of the items
followed. As shown in Table 4, Usefulness and Confidence had Cronbach’s α of 0.869
and 0.763, respectively. These values were higher than the acceptable value of 0.70.
Meanwhile, Gender View was not found reliable since its Cronbach’s α = 0.542.
Though this value is considered acceptable for some researchers, the study aimed a
higher Cronbach’s α. Thus, series of item deletions were performed. Items 3 and 12
were deleted and Gender yield to a higher Cronbach’s α = 0.759.
Step 3 (Second iteration). Factorial validity of the items
Factor validity was repeated since two items in Gender View were deleted. The second
iteration of factor analysis on Gender View revealed that all items were still valid (f.l>=
0.50). Thus, the study achieved the high factorial validity and reliability of the constructs.
4.2.5 Step 5 and 6. Confirmatory factor analysis and development of the final attitude
scales
Confirmatory factor analysis (CFA) was performed to determine if the variables fit in to
the questionnaire. The questionnaire was revised to achieve a good fit. Discriminant
validity was also determined. The final Capstone Project Attitude Scales (CPAS) is
shown in Table 5.
Educ Inf Technol (2015) 20:485–504 495
The final scales were reduced to 15 items. The cumulative variance shows that 57 %
in the attitudes of the students towards Capstone Project could be explained by the
questionnaire. The constructs were found to be of good fit as indicated by the CFI=
0.97, AGFI=0.94, and RMSEA=0.038. Moreover, Table 6 disclosed that all AVEs of
the constructs were greater than the squared correlations of the constructs. Hence,
discriminant validity was achieved.
Table 2 Second draft of the attitude scales
No. Items Subscale
category
1 Capstone Project will help me earn a living. U
2 Capstone Project is important to me in my life’s work. U
3 Males are naturally better than females in Capstone Project. G
4 Capstone Project is a difficult subject. C
5 Females could be good in Capstone Project. G
6 I will need Capstone Project for my future work. U
7 When a female has a Capstone Project, she should have a male group mate. G
8 I am sure of myself when I enrolled Capstone Project. C
9 I don’t expect to use my subject Capstone Project when I get out of school. U
10 Women can do just as well as men in Capstone Project. G
11 Capstone is a worthwhile, necessary subject. U
12 I would have more faith in solving issues by a man than a woman. G
13 I’m not the type to do well in Capstone Project. C
14 Taking the Capstone Project subject is a waste of time. U
15 Capstone Project is the worst subject. C
16 I will use the subject Capstone Project in many ways as a professional. U
17 Females are as good as males in Capstone Project. G
18 I see Capstone Project as something I won’t use very often when I get out of college. U
19 Women certainly are smart enough to do well in Capstone Project. G
20 The skills I will learn in Capstone Project are needed for my future work. U
21 Studying Capstone Project is just as good for women as for men. G
22 Doing well in Capstone Project is not important for my future. U
23 Capstone Project is not important for my life. U
24 I study Capstone Project because I know how useful it is. U
25 I would trust a female just as much as I would trust a male to solve important issues in
Capstone Project.
G
26 I believe that Capstone Project is only for intelligent students. C
27 I like Capstone Project. C
28 Capstone Project is a challenging subject. C
29 I feel lazy whenever I hear the subject Capstone Project. C
30 I am forcing myself to take Capstone Project. C
496 Educ Inf Technol (2015) 20:485–504
Table 3 Factorial validity
Constructs Results
Usefulness f.l.
Capstone Project will help me earn a living. 0.785
Capstone Project is important to me in my life’s work. 0.764
I will need Capstone Project for my future work. 0.747
I don’t expect to use my subject Capstone Project when I get out of school. 0.655
Capstone Project is a worthwhile, necessary subject. 0.587
Taking the Capstone Project subject is a waste of time. 0.687
I will use the subject Capstone Project in many ways as a professional. 0.676
I see Capstone Project as something I won’t use very often when I get out of college. 0.736
The skills I will learn in Capstone Project are needed for my future work. 0.697
Doing well in Capstone Project is not important for my future. 0.791
Capstone Project is not important for my life. 0.751
I study Capstone Project because I know how useful it is. 0.658
Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.898
Bartlett’s Test of Sphericity χ2 2,112.598
df 66
Sig 0.00
Confidence f.l.
Capstone Project is a difficult subject. (deleted) (deleted)
I am sure of myself when I enrolled Capstone Project. 0.717
I’m not the type to do well in Capstone Project. 0.702
Capstone Project is the worst subject. 0.670
I believe that Capstone Project is only for intelligent students. 0.639
I like Capstone Project. 0.672
Capstone Project is a challenging subject. 0.770
I feel lazy whenever I heard the subject Capstone Project. 0.756
I am forcing myself to take Capstone Project. 0.685
Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.817
Bartlett’s Test of Sphericity χ2 748.389
df 28
Sig 0.000
Gender view f.l.
Males are naturally better than females in Capstone Project. 0.720
Females could be good in Capstone Project. 0.759
When a female has a Capstone Project, she should have a male group mate. 0.693
Women can do just as well as men in Capstone Project. 0.754
I would have more faith in a man than in a woman in solving issues in Capstone Project. 0.785
Females are as good as males in Capstone Project. 0.735
Women certainly are smart enough to do well in Capstone Project. 0.705
Studying Capstone Project is just as good for women as for men. 0.717
I would trust a female just as much as I would trust a male to solve important issues in
Capstone Project.
0.707
Educ Inf Technol (2015) 20:485–504 497
Since the number of items was reduced, factorial validity and reliability of the
constructs were repeated. The analysis revealed that all items were still valid and all
constructs were still reliable.
5 Discussion
Capstone Project is one of the core courses in the computing curriculum. It is also a
culminating course that requires soft and technical skills. This requirement, in turn,
makes the course difficult and demanding. Inevitably, students would develop particular
attitudes towards the course. Previous studies showed that attitudes of students
were related to their academic performance (e.g., Craker 2006; Mettas et al. 2006;
Petscher 2010; Nasr and Soltani 2011; Bringula 2012). Despite these pressing concerns,
attitudes of students towards Capstone Project have not yet been investigated. This is
partly attributed to the absence of valid and reliable attitude scales for Capstone Project.
This study attempted to fill in this gap by developing the CPAS. CPAS was based on
MFSMAS. However, throughout the course of study, items of MFSMAS could not
wholly fit on the context of the study due to the nature of the course. Statements that
could not be answered by some students, ethical considerations, redundancy of statements,
and unfit item scale were issues encountered during the development of CPAS.
Hence, the original 47-item scales of MFSMAS were revised and were reduced to 30-
item scales.
The high factor loadings on all constructs showed that the items on each construct
measured what was really intended to be measured on that construct. In other words,
the survey form was simply asking the right questions. The items “Capstone Project is
important to me in my life’s work”, “I feel lazy whenever I heard the subject Capstone
Project”, and “Females are as good as males in Capstone Project” had the highest
factor loadings in the constructs Usefulness, Confidence, and Gender View,
Table 3 (continued)
Constructs Results
Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.849
Bartlett’s Test of Sphericity χ2 1,158.892
df 36
Sig 0.00
Table 4 Reliability of the items
Constructs No. of items Cronbach’s α (First Run) Cronbach’s α (Second Run)
Usefulness 12 0.869 0.869
Confidence 8 0.763 0.763
Gender View 9 0.542 0.759
498 Educ Inf Technol (2015) 20:485–504
Table 5 Final capstone project attitude scales
Capstone project attitude scales f.l.
Usefulness (α = 0.837)
1. Capstone Project will help me earn a living. 0.795
2. Capstone Project is important to me in my life’s work. 0.804
3. I will need Capstone Project for my future work. 0.786
4. I will use the subject Capstone Project in many ways as a professional. 0.654
5. The skills I will learn in Capstone project are needed for my future work. 0.657
Confidence (α = 0.748)
1. I’m not the type to do well in Capstone Project. 0.706
2. Capstone Project is the worst subject. 0.655
3. I believe that Capstone Project is only for intelligent students. 0.656
4. I feel lazy whenever I heard the subject Capstone Project. 0.735
5. I am forcing myself to take Capstone Project. 0.696
Gender view (α = 0.818)
1. Females could be good in Capstone Project. 0.740
2. Women can do just as well as men in Capstone Project. 0.759
3. Females are as good as males in Capstone Project. 0.792
4. Women certainly are smart enough to do well in Capstone Project. 0.775
5. I would trust a female just as much as I would trust a male to solve important issues in Capstone Project. 0.659
%cumulative variance=57 %
Comparative-fit index (CFI)=0.97
Adjusted goodness-of-fit index (AGFI)=0.94
Root mean square error of approximation (RMSEA)=0.038
Educ Inf Technol (2015) 20:485–504 499
respectively. These items had the highest contributions in explaining the constructs and
in vividly describing the attitudes of the students towards the course.
CPAS could capture more than half of the attitudes exhibited of the students
in the course as shown by the percentage of cumulative variance. It also shows
that there are other items or subscales that could be included in the present
attitude scales.
Also, the high values of KMO revealed that the sampling size of the study
was adequate, thus warranting the use of factor analysis. The Barlett’s Test of
Sphericity on all constructs was found significant at 0.05 level of significance.
This means that the items under each construct did not produce an identity
matrix. Hence, all items were suitable to that construct. In other words, all
items on each construct were related to one another. The Cronbach’s α of
Usefulness (Cronbach’s α = 0.869), Confidence (Cronbach’s α = 0.763), and
Gender View (Cronbach’s α = 0.759) were all greater than the threshold value
of 0.70. The result suggested that all items on the constructs were all reliable.
Therefore, the scores that could be obtained from these constructs would be
consistent from the administration of one survey to another.
Confirmatory test also showed that CPAS had a good fit after some modifications
have been made on the items. Items that were not suitable in the
model were dropped until a good fit model was achieved. Results showed that
the cut-offs of good fit model (CFI=0.97, AGFI=0.94, and RMSEA=0.038)
were all met. As shown in Table 6, all squared correlations were lower than the
AVEs of all constructs. Such result indicated that discriminant validity existed.
This finding revealed that the constructs were unrelated and they uniquely
contributed to understanding the attitudes of students towards the course. Thus,
it was concluded that CPAS was composed of three good-fit constructs with
fifteen (15) valid and reliable items. Overall, the findings of the present study
provided evidence for the factorial validity, reliability, and good-fit model of
the CPAS. Therefore, the developed scales could now be utilized in determining
of the attitudes of the students towards Capstone Project.
The developed CPAS had three facets of attitudes towards Capstone Project. The
first construct (i.e., Usefulness) intended to determine how students perceived the
importance of Capstone Project in their future career and profession. Also, it aimed
Table 6 Capstone Project attitude constructs correlation matrix
Variables Usefulness Gender Confidence
Usefulness 1.00 0.16 0.19
Gender 0.40 1.00 0.02
Confidence −0.44 −0.14 1.00
Values below the diagonal are correlation estimates among construct, diagonal elements are construct
correlations, and values above the diagonal are squared correlations
AVE (Usefulness)=0.49
AVE (Gender)=0.48
AVE (Confidence)=0.37
500 Educ Inf Technol (2015) 20:485–504
to measure students’ perception on the impact of the course in terms of earning a living.
This is similar to the construct in the developed scales of Tapia and Marsh (2000),
Doepken et al. (2003), Yara (2009), and Tekerek et al. (2011). The possible impact of
this construct is that it could describe the attitudes of the students towards the course and
it could determine the students’ perception on the practicality of the course. For
example, the studies of Ramirez (2005), and Coetzee and Van derMerwe (2010) showed
that even if the students had difficulty with mathematics subject, they still perceived that
the subject was important. These studies could be replicated using CPAS.
Similar to the scales developed by Tapia and Marsh (2000), Doepken et al. (2003),
Asante (2012), Yara (2009), Coetzee and Van der Merwe (2010), and Mohd and
Mahmood (2011), the Confidence construct served as a form of students’ self-esteem
and competence assessment. It was shown that confidence towards a subject was
related to the students’ academic performance (e.g., Coetzee and Van der Merwe
2010; Bringula et al. 2012). However, researchers in the field of computing could not
verify if this was also true in Capstone Project. Thus, CPAS is a promising datagathering
tool for this research gap.
Lastly, the purpose of the construct Gender— a unique component of the questionnaire
developed by Doepken et al. (2003)—was to determine if the students were
gender-biased in the context of the course. Unlike in the fields of science and mathematics
where stereotyping has been shown to exist (see LaLonde et al. 2003; Cracker
2006; Meece et al. 2006; Brandell and Staberg 2008), studies that showed whether
stereotyping existed in computing degree programs were very scarce. Thus, the
practical value of CPAS is that if students were found gender-biased towards the role
of women in Capstone Project, then administrators and teachers/advisers could correct
these perceptions. A program that highlights the importance of cooperation of both
genders could be initiated. Hence, stereotyping could be avoided.
6 Conclusions, limitations, and future research
It was shown that the Modified Fennema-Sherman Mathematics Attitude Scale could
serve as basis in the formulation of Capstone Project Attitude Scales. Out of the original
47 items, 15 items were retained. The developed attitude scales could capture 57 % of
the students’ attitudes towards Capstone Project. It was revealed that the constructs had
a good fit model and the retained items were all valid and reliable. The study calls for
further modifications of the developed scales to determine the other dimensions of
attitudes towards Capstone Project. It is recommended that cognitive, affective, and
behavioral dimensions be included in the developed scales. It is also encouraged that
the study be replicated by other foreign and local universities in order to come up with
more generalized attitude scales.
With the use of the developed scales, students’ attitudes towards Capstone Project
can now be determined. The outcomes of this study could serve as basis in the
development of educational programs or policies in sustaining the students’ positive
attitudes towards Capstone Project and reversing the negative attitudes. Attitudinal
differences on Capstone Project between males and females could also be investigated.
Lastly, the relationship between students’ attitudes towards Capstone Project and their
performance on the course could also be explored.
Educ Inf Technol (2015) 20:485–504 501
Acknowledgements The author is greatly indebted to Dr. Ester A. Garcia, Dr. Linda P. Santiago, Dr. Olivia
C. Caoili, Dean Rodany A. Merida, Dr. Socorro R. Villamejor, and to the Research and Development Unit
members of the College of Computer Studies and Systems.
References
Abbas, R. Z., Ashraf, M., Ahmad,M., Khalil, U., & Ahmad, Z. (2011).Measuring the attitude towards science
in Pakistan: A study of secondary school students. Interdisciplinary Journal of Contemporary Research in
Business, 2(10), 98–117.
Abdullah, A. H., & Zakaria, E. (2011). An exploratory factor analysis of an attitude towards geometry survey
in a Malaysian context. International Journal of Academic Research, 3(6), 190–193.
Asante, K. O. (2012). Secondary students’ attitudes towards mathematics. Ife PsychologIA, 20(1), 121–133.
ABET. (2012). Criteria for accrediting engineering programs. Retrieved January 28, 2013, from http://www.
abet.org/uploadedFiles/Accreditation/Accreditation_Step_by_Step/Accreditation_Documents/Current/
2013_-_2014/eac-criteria-2013-2014.pdf.
Beer, J. M., McBride, S. E., Adams, A. E., & Rogers, W. A. (2011). Applied experimental psychology: A
capstone course for undergraduate psychology degree programs. Proceedings of the Human Factors and
Ergonomics Society Annual Meeting, 55, 535–539. doi:10.1177/1071181311551109.
Brandell, G., & Staberg, E.-M. (2008). Mathematics: A female, male or gender-neutral domain?: A study of
attitudes among students at secondary level. Gender and Education, 20(5), 495–509. doi:10.1080/
09540250701805771.
Brandon, D., Pruett, J., & Wade, J. (2002). Experiences in developing and implementing a capstone course in
Information Technology Management. Journal of Information Technology Education, 1(2), 91–102.
Bringula, R. P., Tolentino, M. A. A., Manabat, G.M. A., & Torres, E. L. (2012). Effects of attitudes towards Java
programming on novice programmers’ errors. Philippine Information Technology Journal, 5(1), 29–34.
Coetzee, S., & Van der Merwe, P. (2010). Industrial psychology students’ attitudes towards statistics. SA
Journal of Industrial Psychology/SA Tydskrif vir Bedryfsielkunde, 36(1), Art. 843, 8 pages. doi: 10.4102/
sajip.v36i1.843.
Craker, D. E. (2006). Attitudes toward science of students enrolled in introductory level science courses at
UW-La Crosse. UW-L Journal of Undergraduate Research, 29, 1–6.
Doepken, D. Lawsky, E., & Padwa, L. (2003). Modified Fennema-Sherman attitude scales. Paper presented at
Gender Equity for Mathematics and Science: A Conference of the Woodrow Wilson Leadership Program for
Teachers. Retrieved February 5, 2013 from http://www.woodrow.org/teachers/math/gender/08scale.html.
Duatepe, A., & Çilesiz, Ş. (1999). Matematik tutum ölçeği geliştirilmesi. Hacettepe Üniversitesi Eğitim
Fakültesi Dergisi, 16, 45–52.
Feldt, R. C. (2013). Factorial invariance of the indecision scale of the career scale: A multigroup confirmatory
factor analysis. The Career Development Quarterly, 61(3), 249–255. doi:10.1002/J.2161 -0045.2013.
00053.x.
Field, A. (2009). Discovery statistics using SPSS (3rd ed.). London: Sage Publications.
George, D., & Mallery, P. (2009). SPSS for Windows step by step: A simple guide and reference 16.0 update
(9th ed.). Boston: Pearson Education.
Haddock, G., & Maio, G. R. (2007). Attitudes. In Encyclopedia of social psychology (Vol. 1, pp. 67–69).
Thousand Oaks, CA: Sage Publications Inc.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.).
Singapore: Pearson Education South Asia Pte Ltd.
Hartzel, K. S., Spangler, W. E., Gal-Or, M., & Jones, T. H. (2003). A case-based approach to integrating an
Information Technology curriculum. Information Systems Education Journal, 1(47), 1–9. Retrieved
November 13, 2012, from http://isedj.org/1/47/.
Kahveci,M. (2010). Students’ perceptions to use technology for learning: Measuring integrity of the modified
Fennema-Sherman attitude scales. TOJET: The Turkish Online Journal of Educational Technology, 9(1),
185–201.
Kordi, A., & Baharudin, R. (2010). Parenting attitude and style and its effect on children’s school achievements.
International Journal of Psychological Studies, 2(2), 217–222.
Kumar, A., Baker, K., & Ahmed, I. (2004). Designing a capstone course for Information Systems: Challenges
faced and lessons learned. Issues in Information Systems, 5(1), 173–179.
502 Educ Inf Technol (2015) 20:485–504
LaLonde, D., Leedy, M. G., & Runk, K. (2003). Gender equity in mathematics: Beliefs of students, parents
and teachers. School Science and Mathematics, 103(6), 285–292.
Liman, M. A., Ibrahim, M. B., & Shittu, A. T. (2011). Exploraory factor analysis: Validation of mathematical
values inculcation model among secondary schools’ mathematics teachers in North-Eastern Region,
Nigeria. Interdisciplinary Journal of Contemporary Research in Business, 3(1), 63–72.
Lunt, B. M, Ekstrom, J. J., Gorka, S., Hislop, G., Kamali, R., Lawson, E., LeBlanc, R., Miller, J, & Reichgelt,
H. (2008). Information Technology 2008: Curriculum guidelines for undergraduate degree programs in
Information Technology. Retrieved December 10, 2012, from http://www.acm.org/education/curricula/
IT2008%20Curriculum.pdf.
Maleki, M. R., Delgoshaie, B., Nasiripour, A. A., & Yaghoubi, M. (2012). Exploratory and confirmatory
factor analysis of health promotion in Iranian hospitals. HealthMED, 6(7), 2261–2267.
Matwin, S., & Fabrigar, L. R. (2007). Attitudes test. In Encyclopedia of measurement and statistics (Vol. 1, pp.
53–56). Thousand Oaks, CA: Sage Reference.
McGann, S. T., & Cahill, M. A. (2005). Pulling it all together: An IS capstone course for the 21st century
emphasizing experiential & conceptual aspects, soft skills and career readiness. Issues in Information
Systems, 6(1), 391–397.
Meece, J., Glienke, B. B., & Burg, S. (2006). Gender and motivation. Journal of School Psychology, 44(5),
351–373. doi:10.1016/j.jsp.2006.04.004.
Mettas, A., Karmiotis, I., & Christoforou, P. (2006). Relationship between students’ self-beliefs and attitudes
on science achievements in Cyprus: Findings from the Third International Mathematics and Science
Study (TIMSS). Eurasia Journal of Mathematics, Science and Technology Education, 2(1), 41–52.
Meyer, D. G. (2005). Capstone design outcome Assessment: Instruments for quantitative evaluation. Paper
presented at the Frontiers in Education’05: 35th ASEE/IEEE Frontiers in Education Conference (pp.
F4D-7-F4D-11). Retrieved November 15, 2012, from IEEE Xplore. doi: 10.1109/FIE.2005.1612136.
Miles, G., & Kelm, K.M. (2007). Capstone project experiences: Integrating Computer Science and the Liberal Arts.
Information Systems Education Journal, 5(30), 1–10. Retrieved November 15, 2012, from http://isedj.org/5/30/.
Mohd, N., & Mahmood, T. F. P. T. (2011). The effects of attitudes towards problem solving in mathematics
achievements. Australian Journal of Basic and Applied Sciences, 5(12), 1857–1862.
Moshkovich, H. M. (2012). Development project vs. Research project in an MIS capstone course: Student
perceptions. Review of Business Research, 12(2), 140–144.
Nasr, A. R., & Soltani, K. A. (2011). Attitude towards biology and its effects on student’s achievement.
International Journal of Biology, 3(4), 100–104. doi:10.5539/ijb.v3n4pl00.
Orhun, N. (2007). An investigation into the mathematics achievement and attitude towards mathematics with
respect to learning style according to gender. International Journal of Mathematical Education in Science
and Technology, 38(3), 321–333.
Ozturk, M. A. (2011). Confirmatory factor analysis of the educators’ attitudes toward educational research
scale. Educational Sciences: Theory and Practice, 11(2), 737–747.
Payne, S. L., Flynn, J., & Whitfield, J. M. (2008). Capstone business course assessment: Exploring student
readiness perspectives. Journal of Education for Business, 83(3), 141–146.
Petscher, Y. (2010). A meta-analysis of the relationship between student attitudes towards reading and
achievement in reading. Journal of Research in Reading, 33(4), 335–355.
Ponticell, J. A. (2006). Attitudes towards work. In Encyclopedia of educational leadership and administration
(Vol. 1, pp. 62−63). Thousand Oaks, CA: Sage Reference.
Ramaswami, S., & Babo, G. (2012). Investigating the construct validity of the ISLLC 2008 standards through
exploratory factor analysis. International Journal of Educational Leadership Preparation, 7(2), 1–15.
Ramirez, M. J. (2005). Attitudes toward mathematics and academic performance among Chilean 8th graders.
Estudios Pedagógicos, 31(1), 97–112.
Russell, J., Russell, B., & Tastle, W. J. (2005). Teaching soft skills in a systems development capstone class.
Information Systems Education Journal, 3(19), 1–23. Retrieved December 10, 2012, from http://isedj.org/3/19/.
Salinas, M. F. (2006). Attitudes. In Encyclopedia of human development (Vol. 1, pp. 140–142). Thousand
Oaks, CA: Sage Reference.
Shelley, M. C. (2006). Attitudes. In Encyclopedia of educational leadership and administration (Vol. 1, pp.
61–62). Thousand Oaks, CA: Sage Reference.
Tapia, M., Marsh, & G. E. II (2000). Attitudes toward mathematics instrument: An investigation with middle
school students. Paper presented at the Annual Meeting of the Mid-South Educational Research
Association (pp. 1–15). Retrieved November 15, 2012, from Eric database.
Tapia, M., & Marsh, G. E., II. (2004). An instrument to measure mathematics attitudes. Academic Exchange
Quarterly, 8(2). Retrieved January 3, 2013, from http://www.rapidintellect.com/AEQweb/cho25344l.htm.
Educ Inf Technol (2015) 20:485–504 503
Tekerek, M., Yeniterzi, B., & Ercan, O. (2011). Math attitudes of computer education and instructional
technology students. TOJET: The Turkish Online Journal of Educational Technology,
10(3), 168–174.
Yara, P. O. (2009). Students attitude towards mathematics and academic achievement in some
selected secondary schools in Southwestern Nigeria. European Journal of Scientific Research,
36(3), 336–341.
504 Educ Inf Technol (2015) 20:485–504

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Ini merupakan kali pertama Ariana Grande menyambangi Indonesia untuk menggelar konser. Tak heran, antusiasme para Arianators begitu heboh bahkan sebelum konser berlangsung.

Ariana Grande nampak begitu terkesan dengan kehadiran dan dukungan dari Arianators yang hadir pada konser. Ia juga mengukapkan rasa terima kasih melalui akun Twitter pribadinya.

Ariana juga menuliskan bahwa Arianators Indonesia menyanyikan setiap kata dengan sangat lantang. Ariana tersentuh dengan reaksi Arianators yang begitu hanyut akan penampilan pelantun lagu Problem ini.

Beberapa waktu kemudian, Ariana kembali menulis tweet bahwa ia sangat lelah. Bagaimana tidak, Ariana Grande beraksi di panggung The Honeymoon Tour di Indonesia dengan sangat prima dan enerjik. Tak heran, jika setelah konser ia merasa kelelahan.

Ariana Grande sukses merebut hati Arianators Indonesia dengan membuka konser bersama lagu Bang Bang. Menjelang konser usai, Ariana melantunkan Honeymoon Avenue, Break Free dan diakhiri dengan lagu Problem.

Katrina Kaif Puji Calon Ayah Mertua

Bintang Bollywood Katrina Kaif buka-bukaan tentang laki-laki yang mungkin menjadi ayah mertuanya suatu hari nanti. Pada hari Selasa (25.8/2015), Hindustan Times membagikan wawancara bersama Katrina.

Di wawancara itu, Katrina memuji Rishi Kapoor, ayah dari kekasihnya, Ranbir Kapoor. Terlepas dari mereka akan menjadi sebuah keluarga atau tidak, Katrina hanya memiliki hal baik untuk dikatakan tentang Rishi.

“Aku telah bekerja dengan Rishi di Namastey, London dan dia super baik kepadaku,” katanya. “aku pikir dia mengagumkan, menarik, orang eksentrik. Dia adalah legenda yang hidup dan aku merasa senang ketika aku melihatnya.”

Sayangnya, Katrina menjelaskan jika tidak ada rencana untuk menikah dengan Ranbir. Setidaknya dalam waktu dekat ini.

“Belum ada rencana pernikahan. Aku tidak mengerti mengapa orang-orang tergesa-gesa, mendorong kami untuk menikah. Pernikahan harus terjadi ketika waktunya tepat untuk keduanya,” tutur Katrina.

Ternyata, ini bukan kali pertama Katrina mengungkapkan bahwa dia tidak sedang mempersiapkan pernikahan. Dalam sebuah pemberitaan oleh Masala, dia sekali lagi menyatakan ingin menjadi istri suatu hari nanti, tapi tidak pada saat ini.

“Aku pasti ingin pernikahanku menjadi acara besar,” kata Katrina Kaif. Tidak ada keraguan tentang hal itu. Hanya tidak sekarang. Dan aku tidak mengerti mengapa orang begitu bersemangat tentang pernikahan seorang aktor atau mengapa mereka ingin seorang perempuan untuk menikah segera?”

Hasil Drawing Fase Grup Liga Champions 2015-2016

UEFA baru saja menuntaskan undian untuk menentukan klub-klub yang akan bertarung di fase grup Liga Champions musim 2015-2016 mendatang.

Acara pengundian itu dilangsungkan di markas UEFA di Nyon, Swiss, pada hari Kamis (27/08) ini. Legenda Manchester United, Peter Schmeichel, turut hadir untuk menjadi host di acara tersebut.

Dua legenda dari AC Milan dan Inter Milan, Paolo Maldini dan Javier Zanetti, turut melakukan pengundian di acara tersebut. Begitu pula dengan legenda Barcelona, Carles Puyol.

Juara musim lalu, Barcelona, diundi masuk grup E. SementaraJuventus yang menjadi lawan Blaugrana di final musim lalu masuk grup D. Real Madrid, sang kolektor piala terbanyak di ajang kompetisi ini, masuk ke grup A.

Berikut hasil lengkap pengundian babak grup Liga Champions untuk musim 2015-2016:

• Grup A: PSG, Real Madrid, Shakhtar Donetsk, Malmo FF
• Grup B: PSV Eindhoven, Manchester United, CSKA Moscow, Wolfsburg
• Grup C: Benfica, Atletico Madrid, Galatasaray, Astana
• Grup D: Juventus, Manchester City, Sevilla, Borussia Monchengladbach
• Grup E: Barcelona, Bayer Leverkusen, AS Roma, BATE Borisov
• Grup F: Bayern Munich, Arsenal, Olympiakos, Dinamo Zagreb
• Grup G: Chelsea, Porto, Dynamo Kiev, Maccabi Tel Aviv
• Grup H: Zenit St Petersburg, Valencia, Lyon, Gent

Laga final Liga Champions untuk musim 2015-2016 ini akan dilangsungkan stadion San Siro, 28 Mei mendatang.

The WalkAbout framework for contextual learning through mobile serious games

Fernando Almeida & Hiram Bolaert & Shane Dowdall & Justino Lourenço & Piotr Milczarski
Published online: 8 November 2013 # Springer Science+Business Media New York 2013
Abstract Learning through games is increasingly gaining acceptance as a valuable training tool within the education and training community due to its simplicity, cost- effectiveness and essentially because most people prefer playing over learning. However, the use of games by students brings additional challenges regarding the design of games and their adoption in different learning, academic and interdisciplinary contexts, where issues such as planning, teachers and students participation have an important role in the success of contextual learning initiatives. This paper introduces a novel development framework and a learning process called WalkAbout for contextual learning mobile game systems that enables learners to practice and enhance 21st century skills, while generating and playing mobile contextual games. In our research, we investigate the main issues regarding the process of creating contextual mobile games and we detail the adopted methodology used in the design and implementation process of the WalkAbout framework. Finally, in order to preliminarily validate the platform and adopted methodology, we present and discuss the main results obtained
Educ Inf Technol (2015) 20:415–428 DOI 10.1007/s10639-013-9292-6
F. Almeida (*):J. Lourenço Polythenic Institute of Gaya, ISPGaya, Vila Nova de Gaia, Portugal e-mail: falmeida@ispgaya.pt
J. Lourenço e-mail: jml@ispgaya.pt
H. Bolaert Artesis Hogeschool Antwerp, Antwerp, Belgium e-mail: hiram.bollaert@artesis.be
S. Dowdall Dundalk Institute of Technology, Dundalk, Ireland e-mail: Shane.Dowdall@dkit.ie
P. Milczarski University of Lodz, Lodz, Poland e-mail: piotr.milczarski@uni.lodz.pl
after the games development, by looking at the potential of our design approach, the software framework and the learning experience that was offered to the students.
Keywords Contextuallearning.Mobileplatforms . Seriousgames .Multimedia . Multidisciplinaryeducationalexperience
1 Introduction
Serious games have an explicit and central educational purpose and are not intended to be played primarily for amusement. Michael and Chen (2006) consider that a“serious game is a game in which education (in its various forms) is the primary goal, rather than entertainment”. Zyda (2005) proposes a similar definition, though with more detail as to the nature of the purpose: “serious games is a mental contest, played with a computer in accordance with specific rules, that uses entertainment to further government or corpo- rate training, education, health, public policy, and strategic communication objectives”. When adopting computer games—and games in general—for educational purposes, several aspects of the learning process are supported: learners are encouraged to combine knowledge from different areas to come up with a solution or to make a decision at a certain point, learners can test how the outcome of the game changes based on their decisions and actions, learners are encouraged to contact other team members and discuss and negotiate subsequent steps, thus improving, among other things, their social skills (Pivee et al. 2003). According to Williamson and Sandford (2005) when we are playing serious games, information and sensations experienced make strong impressions and let the player improve perception, attention and memory, promoting behaviour changes through “learning by doing”. In fact, internalizing something that the user did is simpler than learning during traditional frontal lessons, a so-called “passive learning” approach. In a simulated environment it is possible to reduce fear and face a new situation thus increasing user’s confidence in his competency and efficacy. There is currently an increased demand for greater interactivity to be built into learning materials, to offer a variety of different knowledge presentations and to create opportunities to apply knowledge within a virtual world, thus supporting and facilitat- ing the learning process. As a consequence, learning is becoming mobile, and location becomes an important context, both in terms of the physical whereabouts of the learner and also the opportunities for learning to become location-sensitive. The properties and affordances of one’s location vary enormously and hence other contexts become even more important, such as the task, the goal or the user; the ubiquity of network access (GPS, Wifi, Near Field Communication (NFC), etc.); the time of the year or day and even the weather (Brown 2010). Mobile learning refers to the use of mobile or wireless devices for the purpose of learning while on the move (Park 2011). Mobile devices enable learning to take place at any time, in any location, and at a learner’s pace. Klopfer and Squire (2008) describe five properties of mobile handheld devices that produce unique educational affordances: portability, social interactivity, context sensitivity, connectivity, and indi- viduality. Furthermore, several authors such as Specht (2009), Wang (2004) and Yau et al. (2010) recognizes that context is the most distinctive feature in mobile learning.
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Context-aware mobile learning applications leverage the contextual information of the learner to provide personalized and motivating learning experiences. There are many challenges for those who would create contextual learning experi- ences with the natural environment. How can we create immersive learning environ- ments? How can we facilitate the interaction between students? How can we transmit the feeling that the user is controlling their games? How can we assure that the game is effectively helping students in their learning process? This paper presents a novel framework and the learning process to produce contex- tual learning mobile game systems that looks and responds to the identified issues above. Section 2 gives an overview of the state of the art in terms of contextual, mobile and ubiquitous learning. In section 3 we describe the adopted methodology and in section 4 we present the main results obtained in the WalkAbout initiative. Furthermore, insection 5 we discuss the potentialofour design approach, the software framework and the learning experience that was offered to the students.
2 Literature review
2.1 Contextual learning
Context can be broadly defined as the formal or informal setting in which a situation or event occurs. It can include many aspects or dimensions, such as location, date, time, personal and social activity, resources, and goals and task structures of groups and individuals. The file of context-aware computing has established a variety of context definitions, mostly starting from location or object context. Johnson (2002) defends that contextual learning and teaching is based on the discovery that students find meaning in their schoolwork when they join the content of academic subjects with the context of daily life. Zimmermann et al. (2007) give a pragmatic definition of context. For them, context of a person or an object can be defined by five distinct parts:
1. Identify context – includes information about objects and users in the real world. With respect to users, their profile can include preferences, acquired-desired competences, learning style, etc.; 2. Time context – ranges from simple points in time to intervals and a complete history of entities; 3. Location context – splits into quantitative and qualitative location models, which allow to work with absolute and relative positions; 4. Activity context – reflect the entities goals, tasks and actions; 5. Relations context – captures the relation an entity has established to other entities, and describes social, functional and compositional relationships.
Contextual learning has the power to help student’s process new information that is given to them in a way that makes sense according to their own world of memory and experience. The importance of this type of learning is that the student’s mind naturally seeks meaning and context in the subjects they are being taught. At the same time, this type of learning can occur in a number of different places: in the classroom, a
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laboratory, a computer lab, outside, or in a place of work (CORD 2001). Due to the flexibility of this type of learning a teacher can design a learning environment, which incorporates many different forms of experience, including social, cultural and psychological.
2.2 Mobile learning
There are various definitions of mobile learning but no one is generally consensual. Dewey (1996) was the first one to address this issue, and defines mobile learning as “a society which is mobile, which is full of channels for the distribution of a change occurring anywhere, must see to it that its members are educated to personal initiative and adaptability”. More recently, Ally (2005) defines mobile learning as “the delivery of electronic materials on mobile computing devices to allow access from anywhere and at any time”. Generally mobile learning has often been viewed as learning mediated through mobile technology. Due to the progress in the field of broadband communication, it is nowadays possible to use network connections nearly everywhere thus allowing a user to be online all the times. Additionally, while the computational power and the storing capabilities increase, the size of today’s mobile devices decreases. According to Bosomworth (2013), the market for mobile devices is growing more and more and in 3 years it should take over desktop internet usage. This mobile revolution is changing everyday life and offers new ways of learning. This also enables educational institu- tions and teachers to harness mobile learning solutions to offer more effective and richer learning experiences. Mobile learning has some properties that depend on the user: the user’s environment and the used technology or device. It is a very time-constrained task delivering context- oriented content. Learning is normally done on-the-fly, which means that it is very fast and occurs mostly during spare time. Thus, the information provided has to be personalized to the needs of the user. Combining contextual and mobile learning we can use context information to choose the most appropriate information or learning material. Furthermore, mobile learning includes multimodal interaction using several technologies handled on the mobile device, like speech recognition, sound, touch gestures, etc. (Pisey et al. 2012). Lastly mobile learning can also support collaboration, where the user contacts their fellow students, friends or experts. Being mobile adds a new dimension to the activities that can be supported, both because of the personal and portable nature of the devices themselves, and because of the kinds of interactions they can support with other learners and the environment. Klopfer et al. (2002) identify five properties of mobile devices that produce unique educational affordances in terms of portability, social interactivity, context sensitivity, connectivity and individuality. Mobile learning provides a potential way forward for the expansion of education programs to larger segments of the population rather than via the traditional eLearning model that has been adopted in much of the developed world. Valk et al. (2010) states that mobile learning allows a method of educational delivery that could be more cost-effective than e-learning methods, not to mention that the ubiquity of mobile phones means that many people are already familiar with mobile phone applications.
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However, if learning is to have a deep impact in the learning process, there are still several issues that should be properly addressed and considered. The former is the need of supporting temporal mobility. Dispersion in time makes it hard to define precisely the start and end of a mobile learning session. Learning scenarios should consider this aspect and support not only the spatial mobility of students, but also their temporal mobility (for example by giving the opportunity to easily stop and resume a session) (George and Lekira 2009). The latter is the importance to integrate mobile applications into global learning systems.Theideahereistoletthelearnereasilyswitchbetweenadesktopapplicationanda mobile application. For that the user interface should be adaptive and the information gathered during mobile use should be reused on desktop applications in order to adapt the learning game to each learner experience (Cochrane 2010; Paredes and Ayala 2012).
2.3 Ubiquitous learning
Ubiquitous learning (u-learning) in contrast to mobile learning is not necessarily bound to mobile devices. In general, u-learning is enabled by an environment that can be accessed in various contexts and situations. As Van’t Hooft et al. (2007) states, u- learning involves learning in an environment where “all students have access to a variety of digital devices and services, including computers connected to the Internet and mobile computing devices, whenever and wherever they need them”. Students in u-learning environments have the potential to increase their learning experiences because they can critically weight their peers’ ideas, react more intention- ally, and check the accuracy of their opinions or assertions. Students benefit by using the opportunity to engage more thoughtfully than they often do when called on to respond on demand in a classroom or on an in-class exam. Similarly teachers have more flexibility in the way they interact, with the capacity to tailor subsequent lessons and responses to meet students where they are, individually and collectively (Yang 2006). AccordingtoYahyaetal. (2010),u-learningshouldhavethefollowing characteristics:
& Permanency – the information remains unless the learners purposely remove it; & Accessibility – the information is always available whenever the learners need to use it; & Immediacy – the information can be retrieved immediately by the learners; & Interactivity – the learners can interact with peers, teachers, and experts efficiently and effectively, through different media; & Context-awareness – the environment can adapt to the learners real situation to provide adequate information for the learners.
Ubiquitous learning can be about the adoption of appropriate technologies for use in traditional education environments such as classrooms, or it may be about the align- ment of ubiquitous platforms with more ubiquitous contexts of learning outside the formal classrooms, like in workplace, in the home or in public places.
2.4 Educational-game design process
Learning can become more effective if it becomes contextual, mobile and ubiquitous. Cordova and Lepper (1996) demonstrated this concept by using some educational
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tasks, where learning embedded in a motivating setting improved learning outcomes and that engagement can facilitate learning. More recently, George and Serna (2011) structured the classification of activities around the main theories and areas of learning relevant to contextual mobile scenarios:
& Behaviourist – activities that promote learning as a change in observable actions; & Constructivist – activities in which learners actively construct new ideas or concepts based on both their previous and current knowledge; & Situated – activities that promote learning within an authentic context and culture; & Collaborative – activities that promote learning through social interaction; & Informal and lifelong – activities that support learning outside a dedicated learning environment and formal curriculum; & Learning and teaching support – activities that assist in the coordination of learners and resources for learning activities.
George and Serna (2011) established that for the creation of a successful game-based learning opportunity, the following steps of game design, elements of learning and engagement should be taken into consideration:
& Determine pedagogical approach – when designing an educational game we have to reflect upon didactical approach and related topics; & Situate the task in a model world – students should be able to discover meaningful relationships between abstract ideas and practical applications in the context of the real world; concepts are internalized through the process of discovering, reinforc- ing, and relating; & Elaborate the details – educators should choose and design learning environments that incorporate as many different forms of experience as possible (social, cultural, physical and psychological) in working toward the desired learning outcomes; & Map learning activities and concepts to interface actions and objects – the idea is to create polished products and activities valuable in their own right, enabling the learning process to occur in a real world scenario.
There are many interactive learning techniques that have already been used in game based learning. According to Prensky (2000), one of those techniques is “learning from mistakes”, where failure is considered a point where the user gets some feedback. In game based learning making a mistake is a primary way to learn and is considered the motivation for players to keep on trying. Additionally, students should also be able to assess their own activities to see how they are doing and to be able to evaluate their decisions and actions. There must be a close link between action and feedback, which will motivate students to keep playing the game.
3 Methodology
The working method for this project was design-based research. Based on the teaching, coaching and managing experiences of the participating lecturers, a rough working method was set up in which different teams of students needed to collaborate. As a part
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of the working method students were free to team up. Only one specification was given, each member must come from a different country. Initially 8 groups of 5 (or 4) students were formed and were assigned a mentor. The resulting teams were quite different in formation. One team had only male students, and another team was mono-disciplinary. All teams were then formally informed on the task at hand, to build a mobile contextual learning game given the context of the park with its themes and animals. From that point forwards an iterative process of mentoring and giving feedback started. Each morning all mentors briefed each other on the current developments and the overall impression on the progress of the project. During the day all teams were briefed and coached by their mentors. Within the whole group of students two subgroups were identified. The Tech group was responsible for the technical development of the game. On the other side, the Art group was responsible for the learning and multimedia contents. Both groups were regularly called to meet as a group with the Tech mentor and the Art mentor. During those meetings training, feedback and specific instructions were given. The training sessions addressed issues as understanding the gaming system, taking leadership, teambuilding and project management. The members of the Art group were instructed to take leadership over their team and these team leaders were informed on the long term and the short term schedules. WalkAbout IP ran for 10 working days, which is a short time to produce a full scale contextual learning mobile game. Therefore two schedules, one short term and one long term, were defined. The long term planning spanned the 10 days of the project and specified two sprints of 4 days. The short term planning was a day to day planning for the game development, game presentation and the feedback on the teams’ progress. At the end of the first sprint a game demo was presented, after the second sprint, the teams needed to demonstrate indoors a playable game using a mobile device (tablet or smartphone). During the last day of the IP all teams evaluated the working games in the field. Due to the design-based approach the team of lecturers was able to correct and steer the flow of the project. As the project provided a real educational context its results can effectively be used to improve practice in at least a likewise context. The iterative interventions, using mixed methods as training and assessments during the project, were constantly evalu- ated for their effectiveness. The evaluation was done by continuously checking the impact of the interventions on the teams’ progress and the feedback coming back from the students. This year’s IP was a reality check proving that interdisciplinary teams can actually build a playable and challenging contextual mobile game. For subsequent IP’s the framework will be adjusted and enhanced in response to the experiences from the students and the lecturers. In the second IP the focus will move towards instructional design and business plans. The aim will be to realize more complex games and study the marketability of the games. Besides generating more fun contextual mobile games, the goal of the third IP is to attract outsiders to get involved in the building and playing of the games. One achievement would be a website publishing the realized games, offering a ‘do it yourself’ tutorial to attract communities in using the framework to establish more contextual mobile games.
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4 Results
Part of the project intended to analyze the perception of learning while performing a specific task in a specific setting. The setting was an international interdisciplinary team and the task was to build a contextual learning game. During the IP the students were asked to fill out two questionnaires. Two sets of questions were proposed to a group of (Finnish) students during a Quantitative Research Methods course and they derived the final sets of questions which were implemented in the questionnaires. A total of 31 students from our initial group of 40 filled the questionnaires. Six students of 31 responses answered they had already worked in an international interdisciplinary team. These students all indicated that such a team is a powerful working environment although communication and language barriers are the main problem in such a team. Four of these students mentioned they had learned a lot through synergy. Of those students (25 of 31) who had never worked in an international interdisci- plinary team, 22 think working in such a team is very useful, although, they all expect communication and language to be a problem. Almost all (20) are anticipating to learn to collaborate with other people, having a different education, different culture, differ- ent opinion. Except for one student, none had ever built a mobile contextual game. 27 students (of 30 responses) have the opinion that one can learn a lot through building a contextual mobile game. What students think they will learn is very different. Most expectations lie in the line of the student’s current programme. An IT student expects to learn more on javascript and mobile technologies, a student from teacher training expects to learn how to deliver learning content in a more appealing manner and, finally, most students expect to learn to collaborate with people. Only a few students (two of 30) expects to learn something on games/puzzles/challenges and how they are built, one students thinks he will learn something from the context, and five students mention teamwork, time management and organization. When offered a choice of what they expect to learn during the IP they answered as follows in Table 1. Each student was asked to choose maximum three topics. A likewise question about the topics learnt by students (Table 2) was asked in the second questionnaire.
Table 1 Topics expected to learn by students
31 responses in total Absolute frequency Relative frequency
Language 14 15 %
Social 9 10 %
Communication 17 18 %
Team work 21 23 %
Technical 17 18 %
Management 6 7 %
Creativity 7 8 %
Presentation skills 1 1 %
Other 0 0 %
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In two questions students were asked how they experienced relations between teams in terms of competition and collaboration. To the question “How did relations between teams influenced your team [Competition]” one student answer “A little bit in a bad way”, 17 answered“A little bit in a good way” and 12 said “Strongly in a good way”. In relation to the question “How did relations between teams influenced your team [Collaboration (did your team receive help from other teams)]” 3 students answered “A little bit in a bad way”, 13 students answered “A little bit in a good way” and 12 students said “Strongly in a good way”. In an open question on the quality of the teams, some students complained that their team with fewer disciplines (seven ITstudents and 1 non-IT) was considerably weaker in comparison to teams with a richer spread of disciplines (IT, tourism and teacher training). Although the heavy workload, all students were explicitly enthusiastic about their participation and the overall outcome of the IP, wondering what could have been realized in more time considering what they had produced in the present small time frame. We also inquired students about the usefulness of the daily break up meetings and session with mentors. The feedback given by students is shown in Table 3. Another interesting point to analyze is the internal evaluation made by teams regarding the capabilities demonstrated by each student along the project. The overall results of this evaluation about criteria such as initiative, responsibility, time scheduling, attitude to- wardsworkingandcooperationisshowninTable 4.Thelastcolumnindicatestheaverage final score given by external experts during the presentation of the projects by the teams. When we analyze the impact of each criterion in the overall performance of each team, we get the following results depicted in Table 5. The results of Table 5 show that cooperation is the main attribute demonstrated by the teams. On the opposite side, deliver work in time scheduling and initiative were the main issues faced by the teams. There is a clear dependence between the initiative and
Table 2 Topics learnt by students
What did you learn? 30 responses in total
Nothing Superficial (a little)
In depth (a lot)
Language 0 15 (50 %) 15 (50 %)
Social 0 7 (23 %) 23 (77 %)
Communication 0 5 (17 %) 25 (83 %)
Team work 1 (3 %) 3 (10 %) 26 (87 %)
Technical 5 (17 %) 12 (40 %) 13 (43 %)
Management 1 (3 %) 13 (43 %) 16 (53 %)
Creativity 1 (3 %) 7 (23 %) 22 (73 %)
Presentation skills 0 6 (20 %) 24 (80 %)
Game design 4 (13 %) 12 (40 %) 14 (47 %)
Instructional design 5 (17 %) 13 (43 %) 12 (40 %)
Programming/coding 8 (27 %) 13 (43 %) 9 (30 %)
Graphics 8 (27 %) 14 (47 %) 8 (27 %)
Animals (context) 3 (10 %) 11 (37 %) 16 (53 %)
Environmental conservation (context)
5 (17 %) 12 (40 %) 13 (43 %)
Evolution theory (context) 10 (33 %) 8 (27 %) 12 (40 %)
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cooperation demonstrated by the teams in terms of the final results obtained by them. On the opposite side, the responsibility does not show to have a deep impact in the overall quality of work developed by the teams.
5 Discussion
The primary aim of this project was to get students to form international teams and work together on a project. To this end the project was a big success. From the outset the students engaged in the process. Prior to travel, a Facebook page was set up in the hope that the students would start communicating with each other. The Facebook page, introducing WalkAbout IP, was accompanied by two private groups, one for the participating teachers and one for the participating students. All students were invited to become a member of the student group in order to get to know each other and to start forming teams. The Facebook page was initially used to inform all involved about the proceedings of the preparations of the IP. During and after the IP participants used the page to publish team statuses, social activities, pictures. Students also expressed their frustrations and achievements on the page. On the first day of the project, the students arrived at the accommodation, from their various countries, at various times. They knew that the following day they were going to be assigned a team in which there would be at most one person from each country. They were informed that they could form their own teams if they wished and the lecturers would create the teams should
Table 4 Perception of students capabilities distributed by each group
Initiative Responsibility Time scheduling
Attitude towards working
Cooperation Final score (external experts)
Animal quest 4,06 3,88 4,06 3,94 4,31 3,61
Project bird 3,94 3,81 3,88 3,75 4,25 2,78
Beagle 3,88 4,19 4,19 4,13 4,38 2,50
Mobile park 3,81 4,00 3,75 4,13 4,00 2,78
A-team 4,63 4,50 4,63 4,69 4,94 4,72
Make it green 4,20 4,20 4,15 4,20 4,50 3,06
Swift 4,44 4,63 4,25 4,31 4,56 3,33
Table 3 Perception about the use- fulness of feedback sessions
Ranking How useful were the feedback sessions? [Arti/Tech break up]
How useful were the feedback sessions? [sessions with mentors]
Bad 1 (3 %) 0
No use 2 (7 %) 0
Good 16 (53 %) 7 (23 %)
Very good 8 (27 %) 13 (43 %)
Excellent 3 (10 %) 10 (33 %)
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this not happen. We were pleased to hear that they had all met up with each other during that first evening, mingled well and had happily assigned themselves to teams before the end of the night. It was felt that allowing them to form their own teams was an important part of them buying into the process. Based in observational data, was noted that the students tended to hang around with their team members and not their fellow countrymen. Unfortunately, the home country did not quite have the same experience. They were not living in the same accommodation as the others and furthermore their college was still running (evening) classes as normal. This meant that, in general, there was not the same level of participation from those students. This situation helps to understand the low score of criteria initiative and time scheduling (Table 5). A secondary aim was to see if we could get the students to produce a prototype mobile game that would have commercial appeal. Again, the project was a success on this front. While each of the seven teams was given the same context, information and set-up they produced very different but thought-provoking concepts mostly aimed at a younger audience. The variety of concepts included using logic puzzles, puzzles involving sound, moral issues, creating personal databases and education. The com- mercial aspect was evidenced as the National Park requested that two of the games be worked on further with a view to making them a permanent feature. A tertiary aim was to test the capabilities of the chosen framework, WalkAbout. Given that the entire project had to take place during 2 weeks we required a framework that could rapidly turn concepts into games. This framework was designed to use QR codes that, in essence, indexed a database that could be used in both an online and offline setting. WalkAbout is designed to be a platform independent application so a student only need know about HTML5, CSS and JavaScript i.e. no native coding was necessary. The online/offline aspect meant that a person could download a game when they had an internet connection but could then play the game offline. Once an internet connection was re-established other features such as leaderboards could be displayed. This was a highly desirable feature as it allowed games to be played in areas where there was no internet coverage or indeed where it was expensive. Thus, a typical game developed by the students involved scanning a QR code and being asked to solve a puzzle, which in turn led the student to another QR code. While the framework had its limitations some of these helped the teams focus their attention and home in on a concept quickly. It is worth noting that the students came from
Table 5 Impact of students capabilities in the performance of each team
Initiative Responsibility Time scheduling Attitude towards working Cooperation
Mean 4,137 4,173 4,130 4,164 4,420
Biased standard deviation
0,282 0,284 0,262 0,273 0,271
Covariance 0,191 0,108 0,161 0,156 0,171
Correlation 0,843 0,471 0,764 0,706 0,784
Determination 0,710 0,221 0,583 0,499 0,615
T-Test 3,498 1,193 2,645 2,232 2,823
p-value 0,017 0,287 0,046 0,076 0,037
Degrees of freedom 5 5 5 5 5
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a wide variety of backgrounds including tourism, teacher training, applied informatics, games development and telecommunications and there was a wide variety in program- ming skills. That said, each team needed at least one good programmer, as there were many technical issues that needed to be solved during the duration of the project and unfortunately, the documentation was poor. This was offset by having the framework’s creator available during the first week of the project. The need for a good programmer meant that there was a big variety in successfully implementing games. While some managed to produce a fully working prototype others had to abandon the framework altogether and concentrate on the concept. While WalkAbout performed admirably we have learned that we need to be careful in our selection of students so that we get a reasonable balance of technically skilled as well as creative thinkers. Furthermore, it was felt that it would be a good idea to introduce the framework to the technical students in advance. This initiative would help students to increase their learning competences in technical skills, which is one of poorest criterion scored in Table 2. With regards the methodology, it was felt that we managed to bring out the best in the students. They fully engaged with the project and the words ‘Intensive Programme’ was truly fitting. The feedback sessions were considered very useful by our students (Table 3) and let them to share their thoughts and issues regarding the game design and implementation processes. While the output of the students was undeniably excellent there were concerns that maybe it was too intensive. There wasn’t much time set aside for relaxation. Also, there were many instances of students staying up all night working and while they did this out of love of their project one has to question whether this is a desirable feature of future projects. We should also keep in mind that, for most students, this is taking place near the end of an academic semester and when they return to their own college they must re-engage in their normal studies. In looking to the future we need to review the balance between the desirable aspects, the limitations and the goals of this project which include:
& The feeling one gets from producing a high quality and commercially viable product; & The experience of working intensively, within a diverse team, and acquiring the knowledge that this is usually required if a quality product is going to be produced; & The experience has to take place in under 2 weeks; & The primary goal is to get students working in international teams; & The acceptance that some students are nearing the end of their studies and we should not send them home completely exhausted.
While our existing process does a good job of balancing these it is felt that final point needs to be improved. Although efforts were made to allow thorough communi- cation and information towards the students months before the start of the IP, a lot of the information was not received by students. Optimizing communication will allow us to prepare ourselves and the students more and better for the upcoming IP.
6 Conclusions
TheWalkAboutframework has inspired lecturers and studentsof differentnationalities and multidisciplinary domains, from IT fields to design backgrounds and social sciences. The
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WalkAbout framework was deployed and tested by 40 students in total from five interna- tional partners at Parque Biológico of Gaia during 2 weeks of an IP programme. This IP assembled students in the creation of serious and contextual mobile games. Based on a social constructivist view they collaborated in international and interdisciplinary teams. Aiming at the creation of a contextual and mobile game they explored game design, user- interface design, instructional design, multimedia authoring, mobile networking, mobile platform, near field communication (NFC) and quick response (QR) tags. The main focus of this project was not the IT part, but the content creation and the interdisciplinary tasks that created an opportunity for different profile students to cooperate.By focusing onthatsynergy, we could transcend the purelytechnically aspect and make the IP work effectively. Within this IP the mobile devices were used to enhance the behaviouristlearning process.The use ofmobiledevices to present teaching content specify questions (stimulus), obtain responses from learners (response), and provide appropriate feedback (reinforcement) fits within the behaviourist learning paradigm. Additionally, the organization of the students in multicultural and multidis- ciplinary working groups incentivated the acquisition and transfer of knowledge. The results of our project show that given a system to build contextual mobile learning games, an interdisciplinary group with relative technical skills is able to build a challenging and marketable game. Furthermore, the tested framework enables the quick and simple development of any new contextual game approach, as it was shown during the roll-out of the WalkAbout IP. The current framework also makes the game execution totally independent of network coverage and only requires the minimum of hardware to be executed. As future work, building on this year’s experiences, we expect to adjust and enhance the game system, select potential new functionalities, research more complex sets of game rules and adaptability, and study business models where tags are sponsored. Furthermore, the concerns related to network disruptive situations could be addresses, in order to enable real time interactions between players or teams, strongly enriching the game experience. A live connection to social networks could promote the competiveness and enable a faster game spread among all the potential users. Additionally, we also intend to increase and optimize communication among stu- dents and prepare them better to the intensive 2 weeks of an IP project.
References
Ally, M. (2005). Mobile learning anytime anywhere. Proceedings of the MLEARN 2004 conference, Rome, Italy, 5–9. Bosomworth, D. (2013). Mobile marketing statistics 2013. http://www.smartinsights.com/mobile-marketing/ mobile-marketing-analytics/mobile-marketing-statistics/. Accessed June 22, 2013. Brown, E. (2010). Education in the wild: contextual and location-based mobile learning in action. STELLAR Alpine Rendez-Vous Workshop series,7 –19. Cochrane, T. (2010). Exploring mobile learning success factors. Journal of Research in Learning Technology, 18(2), 133–148. CORD. (2001). Learning change in education: What is contextual learning? http://www.cord.org. Accessed June 10, 2013. Cordova, D., & Lepper, M. (1996). Intrinsic motivation and the process of learning: beneficial effects of contextualization, personalization, and choice. Journal of Educational Psychology, 88(1), 715–730. Dewey, J. (1996). Educating the democratic mind. New York: Suny Press.
Educ Inf Technol (2015) 20:415–428 427
George, S., & Lekira, A. (2009). MeCoCo: a context-aware system for mediated communications. International Journal of Interactive Mobile Technologies, 3(1), 26–33. George, S., & Serna, A. (2011). Introducing mobility in serious games: enhancing situated and collaborative learning. Human-Computer Interaction, 6764(part I), 12–20. Johnson, E. (2002). Contextual teaching and learning: What it is and why it’s here to stay. California: Corwin Press. Klopfer, E., & Squire, K. (2008). Environmental detectives—the development of an augmented reality platform for environmental simulations. Educational Technology Research and Development, 56(2), 203–228. Klopfer, E., Squire, K., & Jenkins, H. (2002). Environmental detectives: PDAs as a window into a virtual simulated world. Proceedings of IEEE International Workshop on Wireless and Mobile Technologies in Education, Vaxjo, Sweden, 95–98. Michael, D., & Chen, S. (2006). Serious games: Games that educate, train and inform. Independence: Cengage Learning PTR. Paredes, R., & Ayala, G. (2012). User and context modelling for adaptive mobile learning interfaces. International Journal of Mobile Learning and Organisation, 6(2), 99–115. Park, Y. (2011). A pedagogical framework for mobile learning: categorizing educational applications of mobile technologies into four types. International Review of Research in Open and Distance Learning, 12(2), 78–102. Pisey, M., Ramteke, P., & Burghate, B. (2012). Mobile learning exploring the challenges and opportunities of distance education. World Journal of Science and Technology, 2(3), 19–23. Pivee, M, Dziabenko, O., & Schineerl, I. (2003). Aspects of game-based learning. Proceeding of I-KNOW’03, Graz, Austria, 216–221. Prensky, M. (2000). Digital game-based learning. New York: McGraw-Hill. Specht, M. (2009). Learning in a technology enhanced world. Proceedings of the World Conference on E- learning in Corporate, Government, Healthcare & Higher Education, Montréal, Québec, 1–52. http://hdl. handle.net/1820/2487. Accessed on June 2, 2013. Valk, J., Rashid, A., & Elder, L. (2010). Using mobile phones to improve educational outcomes: an analysis of evidence from Asia. The International Review of Research in Open and Distance Learning, 11(1), 117– 140. Van’t Hooft, M., Swan, K., Cook, D., & Lin, Y. (2007). What is ubiquitous computing? In M. Van’t Hooft & K. Swan (Eds.), Ubiquitous computing in education. New Jersey: Lawrence Erlbaum Associates. Wang, Y. (2004). Context awareness and adaptation in mobile learning. Proceedings of the 2nd IEEE International Workshop on Wireless and Mobile Technologies in Education, Taoyuan, Taiwan, 154–158. Williamson, B., & Sandford, R. (2005). Games and learning: A handbook from Futurelab. Bristol: Futurelab. Yahya, S., Arniza, E., & Kamarularifin, J. (2010). The definition and characteristics of ubiquitous learning: a discussion. International Journal of Education and Development using Information and Communication Technology (IJEDICT), 6(1), 117–127. Yang, S. (2006). Context aware ubiquitous learning environments for peer-to-peer collaborative learning. Educational Technology & Society, 9(1), 188–201. Yau, J., Joy, M., & Dickert, S. (2010). A mobile context-aware framework for managing learning schedules— data analysis from a diary study. Educational Technology & Society, 13(3), 22–32. Zimmermann, A., Lorenz, A., & Oppermann, R. (2007). An operational definition of context. Proceedings of the Sixth International and Interdisciplinary Conference on Modelling and Using Context, Roskilde, Denmark, 558–571. Zyda, M. (2005). From visual simulation to virtual reality to games. Computer, 38(9), 25–32.
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