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.
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