Factors influencing students’ intention to enroll in Bachelor of Science in Biology: A structural equation modelling approach

Abstract

With the declining number of students interested in pursuing STEM courses such as Bachelor’s Degree in Biology as evidenced by low enrollment, HEIs currently offering and those which intend to offer the academic degree program are competing and looking for ways to increase their competitiveness. Hence, several efforts have been made in response to it, including investigating what attracts students to choose the HEI and the course it offers. In this regard, this study aims to evaluate the factors influencing students’ intention to enroll Bachelor of Science (BS) in Biology at Cebu Technological University using an extended Chapman’s Model of Student College Choice. Using a quantitative cross-sectional survey design, 416 senior high-school students from Cebu Province in the Philippines participated in an online survey. The survey aimed to test the influence of student characteristics, influence of significant people, marketing factor, fixed university characteristics, university image, perceived program quality, and perceived career opportunities on students’ intention to enroll in BS Biology. The findings of structural equation modelling suggest that only student characteristics influences students’ intention to enroll the academic degree program. Irrespective of the disassociation of six other proposed hypotheses, the offering of the course is still deemed feasible as supported by students’ responses in their intention to enroll it. In conclusion, this study reveals the model’s usefulness in understanding one of the factors influencing students’ intention to enroll in the course. Consequently, the results offer managerial and theoretical implications to further strategize institutional student recruitment techniques.

Keywords:

• Bachelor of Science in Biology
• student college choice
• feasibility study
• STEM education
• student enrollment

1. Introduction

Developing science, technology, engineering, and mathematics (STEM) competencies becomes essential in responding to an era characterized by rapid technological growth and global challenges. These competencies improve scientific literacy and form a core foundation for responsible citizenship (Maass et al., 2019) and are well recognized in addressing several global socio-scientific problems like global warming, water crises, and ocean acidification (Elías et al., 2022). In addition, these competencies are required for jobs that are key contributors toward national economic growth and international competitiveness (Ahmadov, 2020; Deming & Noray, 2018; Maass et al., 2019; Xie et al., 2015). At present, the role of developing STEM competencies is even more persuasive because of the pandemic. The global health crisis caused by COVID-19 has resulted in an unprecedented volume of STEM knowledge or information that is communicated to the public. However, a large fraction of them willingly ignored scientific judgments about the importance of vaccines, masks, and other health safety protocols in containing the virus (Alberts, 2022). In other words, these people still require the so-called STEM competencies to engage sufficiently with STEM knowledge and to understand how science operates and informs personal health decisions. More so, these competencies are essential to critique the government’s social policy decisions on appropriate behaviors to be observed to limit the spread of the virus (Braund, 2021).

With the global recognition of the growing importance of developing STEM competencies, great emphasis has been placed on STEM as a field study. This results in several educational initiatives and reform efforts focused on attracting students to pursue STEM courses and eventually work on aligned career pathways (Mcdonald, 2016). These efforts include providing merit-based scholarships for incoming college students, engaging them in collaborative research (Piper & Krehbiel, 2015), and transforming secondary schools into academies that allow teachers and students to engage in STEM (Kennedy & Odell, 2014). The latter is accomplished through several initiatives, including offering proactive and strategic approaches to empower teachers with the resources needed to transform teaching and learning methods for the new century. Other practical initiative geared toward increasing enrollment, retention, and graduation in STEM programs, particularly for low-income and talented students with interest in the field, is creating a strong cohort framework for them, developing mentor relationships, and hosting co-curricular activities that promote interaction, learning, and exchange (Shahhosseini et al., 2020). Tsui (2007) also reviewed the literature and reported effective strategies commonly adopted to increase diversity in STEM fields. These are offering pre-college summer bridge or transitional programs that focus on science, mathematics, and engineering subjects, mentoring and tutoring programs, career counseling and awareness, workshop and seminars, academic advising, and financial support. In addition, prospective students are engaged in hands-on STEM-related research, learning centers are established, and curriculum and instruction undergo reforms.

Despite these initiatives, strategies, and reform efforts focusing on STEM, the number of students whose interest in this field has been steadily declining and rejected it as a future career option (Nawawi et al., 2021). As evidence, recent studies reported low student enrollment but high attrition rates in STEM education in higher education (e.g., Kao & Shimizu, 2020; Kayan-Fadlelmula et al., 2022; Sithole et al., 2017). Many STEM entrants end up transferring to non-STEM fields, perform poorly compared to their peers in other academic degree programs, and/or drop out from college (Sithole et al., 2017). As part of the STEM field, this situation does not exempt those students studying biology as a course in college. Some studies reported that many students who entered college with the intent of pursuing a career in the biological or biomedical sciences later abandon this goal or do not finish the academic degree program (Soldner et al., 2012; Tracy et al., 2022). If this situation persists, HEIs, particularly those not funded by the state, that are offering biology programs will suffer in the long run. Lower student enrollments for them mean less revenue and eventually cause yearly deficits to cover the school’s operating expenses (Pavlov et al., 2020). In addition, a high attrition rate impacts an HEIs finances because the cost of retaining an existing student is much less than acquiring a new student (Haverila et al., 2020). A number of causes pointing out students’ declining interest in pursuing biology as a major in college have surfaced. These include but not limited to high-school preparations, academic demands or size of academic requirements both in and out of the class, intrinsic and extrinsic motivations, perceived relevance and confidence, and anxiety in learning biology (Ekici, 2010; Jackson et al., 2022; Ursavas, 2020). This is despite the importance of the discipline in promoting the development of new generations of creative biologists, enhancing environmental literacy, and instilling social responsibility to the citizens (Fleischner et al., 2017).

With the declining number of students interested in pursuing a bachelor’s degree in Biology, low enrollment, and high attrition rate, HEIs currently offering and those which intend to offer the academic degree program are competing and looking for ways to increase their competitiveness. Within the economics of higher education, several efforts have been made not only to recruit prospective and well-qualified students but to investigate what attracts them to choose the HEI and academic degree program. One way is to determine the factors that potentially influence students’ intention to enroll in the proposed or offered academic degree program, which is Bachelor of Science in Biology in the case of the present study. Other than knowing the factor influencing their intention to enroll, this study informs the feasibility of offering the academic program at Cebu Technological University. Eventually, this guides the institution on how to strategize its competitiveness against other HEIs offering the same academic degree program. This study informs its strengths and the areas it needs to improve according to the perspective of the prospective students, who are their most important stakeholders.

2. Literature review

A number of studies have surfaced to enhance our understanding of factors that influence students’ choice of higher education institution (e.g., Gaspar & Soares, 2021; Popov, 2019; Solikhah et al., 2016). However, studies reporting the factors that influence students’ intention to pursue a specific academic degree program or major of specialization are scant or limited because, for one reason, there has been little theory to guide this investigation. In this regard, the lack of a guiding framework for this type of research aim led the present study to adopt Chapman’s (1981) Model of Student College Choice. Although the model is specifically designed to explain the factors that influence prospective students’ choice of which college to attend, it suggests realistic factors that could also be antecedents of students’ intention to pursue a specific academic degree program (e.g., Bachelor of Science in Biology). In particular, it suggests that college choice is influenced by student characteristics and three external factors: the influence of significant people, fixed college characteristics, and the college’s effort to communicate with prospective students. In the present study, these factors are added by three predictor variables (i.e., university image, perceived program quality, and perceived career opportunities) as informed by the literature review while the endogenous variable is modified with the intention to enroll in BS Biology to suit the research aim. The subsequent section discusses the original and the three added predictor or endogenous variables as antecedents of the modified dependent or exogenous variable.

2.1. Student characteristics and their intention to enroll BS in Biology

Student characteristics describe the students in terms of socio-economic status (SES), aptitude and/or high-school performance, and educational aspiration (Chapman, 1981). First, a study revealed that SES affects student choice of an academic degree program in a university where high SES students intend to pursue engineering or sciences. In contrast, low SES students prefer academic degree programs that guarantee immediate job opportunities after graduation (Misran et al., 2012). In other words, students from disadvantaged families may be more sensitive to education costs and may have lower preferences for education (Declercq & Verboven, 2015). Second, aptitude, which refers to high-school achievement and college entrance examination performance, is another variable that Chapman (1981) identified to influence college choice. It is reported that academic ability is used to get a sense of academic confidence and affiliation rather than as an objective measure of ability (Elsner et al., 2021; Huntington-Klein, 2017). Students who perceive themselves with advanced academic ability tend to plan academic degree programs within STEM domain (Rudasill & Callahan, 2010). The level of educational aspiration is also considered to influence college choice. However, while considerable number of literature relates the level of educational aspiration to participation in higher education (Bowers-Brown et al., 2019; Othman et al., 2013), considerably fewer researches relate the level of educational aspiration to academic degree program choice. Lichtenberger and George-Jackson (2013) reported that students with loftier educational aspirations are generally more likely to major in STEM fields in post-secondary education. On the bases of these theoretical supports, this study hypothesizes that:

H₁:

Student characteristics positively and significantly influence students’ intention to enroll BS in Biology.

2.2. Influence of significant people as antecedent of students’ perceived university image, program quality, career opportunities, and intention to enroll in BS Biology

Career choice is a dynamic interplay of youth developmental stages and the prevailing environmental conditions (Howard et al., 2009). It goes through a process of understanding and exploring career options with the help of planning and guidance (Porfeli & Lee, 2012). The guidance may come from family members, teachers and educators, peer influence, and societal expectations or social responsibilities (Akosah-Twumasi et al., 2018; Esters, 2007). In this regard, the influence of significant people or interpersonal factors plays a significant role to deciding what academic degree program to pursue. The parents’ profession, knowledge and income on professional areas or job market they venture, norms, beliefs, information about modern jobs, and the skills they acquire may influence career choice of their children (Saleem et al., 2014). Meanwhile, peers, teachers, and schools are potential enablers for STEM aspirations because they could maintain student interest and achievement levels in sciences and mathematics in the early years of students’ education so that they are able to sustain their belief that pursuing STEM degree or career is achievable (Holmes et al., 2017). These same interpersonal factors could also influence students’ perceptions of the university image, academic degree program quality, and career opportunities as reported by several studies (e.g., Abe & Chikoko, 2020; Malgwi et al., 2005). Thus, the following hypotheses are proposed:

H₂:

Significant people positively and significantly influence students’ perception of the university image.

H₃:

Significant people positively and significantly influence students’ perception of the program quality.

H₄:

Significant people positively and significantly influence students’ perception of the academic degree program career opportunities.

H₅:

Significant people positively and significantly influence students’ intention to enroll BS in Biology.

2.3. University marketing strategy and students’ intention to enroll BS in Biology

Marketing strategy refers to an “organization’s integrated pattern of decisions that specify its crucial choices concerning products, markets, marketing activities and marketing resources in the creation, communication and/or delivery of products that offer value to customers in exchanges with the organization and thereby enables the organization to achieve specific objectives” (Varadarajan, 2010, p. 119). In attracting prospective students to enroll at a program of an institution, one of the recommendations reported by several studies is to adopt effective marketing strategies (e.g., Hung & Yen, 2022; Pokhrel et al., 2016). These may be done by utilizing the school website/social media platforms, quality school programs, infrastructure development, and media adverts because these are modern methods of creating awareness and communicating the institution’s values to prospective students and their parents (Uchendu et al., 2015). According to Bohara et al. (2022), both parents and students visit the website and social media platforms to collect information about the program and institution. The institution may also join university fairs, organize campus visits, and host career fairs as other forms of marketing strategy (Abubakar, 2017; Chapman, 1981; Gaspar & Soares, 2021). Drawing support from these literature, the following hypothesis is proposed:

H₆:

University marketing strategy positively and significantly influence students’ intention to enroll BS in Biology.

2.4. Relatively fixed university characteristics and students’ intention to enroll in BS Biology

Relatively fixed university characteristics pertain to location, costs, campus environment, and availability of the desired program. With the probable exception of location, the remaining three are relatively fixed over a certain period of time, but the institution has the power to change them (Chapman, 1981). In a number of studies, these are generally considered prime considerations when choosing a college and in turn in enrolling to its academic degree program offering along with its facilities, faculty-to-student ratio, and learning resources (Abubakar, 2017; Gaspar & Soares, 2021; Snelling & Boruch, 1970). Accordingly, the following hypothesis is developed:

H₇:

Fixed university characteristics positively and significantly influence students’ intention to enroll BS in Biology.

2.5. University image and students’ intention to enroll in BS Biology

The terms “image” in marketing refers to the actual perceptions by external stakeholders to an organization (Brown et al., 2006). If used in the context in university, Gutiérrez-Villar et al. (2022) relate university image to the functional and affective aspects as well as its reputation. In other words, university image refers to functional and psychological perceptions of stakeholders toward the university. The functional aspect relates to the attributes or benefits linked to the university, such as the quality of its education or training, vision, mission, goals, research, and publication. The affective image covers personality of the university such as its ideological component and the class of person working or studying there. Finally, the reputation pertains to the perception of the university over time in terms of its commitment to community service, ranking over other universities, employability of graduates, and among others. University image has become an increasingly important attribute of any university as what prospective students formed by them greatly influences their choice and eventually maintain their competitiveness in the market (Azoury et al., 2014; Gołata & Sojkin, 2020; Wilkins & Huisman, 2014). It has also become a determinant of how students perceived the quality of its academic degree program offering (Pampaloni, 2010). Thus, the following hypotheses are proposed:

H₈:

University image positively and significantly influence students’ perception of academic program quality.

H₉:

University image positively and significantly influence students’ intention to enroll BS in Biology.

2.6. Students’ perceived program quality and their intention to enrol in BS Biology

The selection of college major or field of specialization is a critical decision that students take. There are several conditions that students take into consideration when deciding a major, or these are referred here as academic degree program quality, such as academic reputation, social status and prestige of the major, opportunity of travelling abroad while pursuing the academic degree program, and among others (Abubakar, 2017; Aldosary & Assaf, 1996). In this regard, students choose the academic degree program to which these conditions can be met. The study of programs and careers within the domain of STEM (e.g., Biology) characterized these conditions, hence, it is increasingly in demand and attractive for students as reported by several studies (Ozis et al., 2018; Sari et al., 2018). In view of this, it is hypothesized that:

H₁₀:

Students’ perceived program quality positively and significantly influence their intention to enroll in BS Biology.

2.7. Future opportunities and students’ intention to enroll in BS Biology

Marketability of career or job opportunities, job satisfaction, financial outcomes or high salaries, prestigious professions, and future benefits are among of the future career opportunities considered when choosing a career (Ahmed et al., 2017; Akosah-Twumasi et al., 2018; Nyamwange, 2016). In other words, students choose an academic degree program that prepares them toward these career opportunities. The study of Biology as an academic degree program may offer these future opportunities if completed; hence, the following hypothesis is proposed:

H₁₁:

Students’ perceived career opportunities positively and significantly influence their intention to enroll in BS Biology.

In summary, the research hypotheses are illustrated in a conceptual framework as presented in Figure 1.

Figure 1. Concept model of the study.

3. Methodology

3.1. Participants

This research was conducted to explore the factors influencing students’ intention to enroll Bachelor of Science (BS) in Biology, a proposed four-year academic degree program in the College of Arts and Sciences at Cebu Technological University (CTU). Eventually, this provided information on the feasibility of opening the academic degree program in the perspective of the students through their intention to enroll. To carry out this aim, a survey was conducted to senior high school (SHS) students within the province of Cebu in the Philippines irrespective of the track they pursue and type of school where they enroll. The survey was employed using convenience sampling technique which resulted in the participation of 416 students. This sample size is already desirable and will provide reasonable results because earlier recommendations by Gerbing and Anderson (1985) and Boomsma (1985) for maximum likelihood estimation technique, respectively, fall only between less than 200 or at least above 100 only. Table 1 reflects the distribution of these SHS students when grouped according to the different socio-demographic profiles.

Table 1. Distribution of participants when grouped according to socio-demographic profiles (n = 416)

Socio-demographic profiles	Category	n	%
Sex	Male	165	39.66
	Female	251	60.34
Grade Level	Grade 11	150	36.06
	Grade 12	266	63.94
Type of secondary school where enrolled	Private	142	34.13
	Public	251	60.34
	Science High School	23	5.53
Track enrolled	Academic	326*	78.37
	Technical-Vocational Livelihood	90	21.63
Type of academic strand enrolled (n = 326)	Science, Technology, Engineering, Mathematics (STEM)	237	72.70
	Business, Accountancy, Management (BAM)	20	6.14
	General Academic Strand (GAS)	42	12.88
	Humanities, Education, Social Sciences (HESS)	27	8.28
Area of residence	Northern	109	26.20
in Cebu	Central or within the tri-cities	234	56.25
	Southern	73	17.55

As seen in the table, almost two-thirds of the participants are female (60.34%), on twelfth grade (63.94%), and enrolled in public school (60.34%) when grouped according to sex, grade level, and type of secondary school where enrolled, respectively. With respect to their distribution when grouped based on the track they enroll, 78.37% are from academic track and 21.63% are from TVL. There was no survey response received from students taking sports and arts and design tracks, although they were invited to participate in the survey. The researchers recognized that some students may still enroll to the proposed BS Biology even if their SHS preparation is not aligned. Besides, the higher education institutions in the Philippines are mandated to admit students in the academic degree program they intend to pursue regardless of the track they finished in SHS. Then, those students who indicated “academic” as the track they pursue in SHS were further asked to indicate their strand of which 72.70% of them were taking STEM and 27.80% are Non-STEM (i.e., BAM, GAS, and HESS). Finally, in the case of their distribution in terms of area of residence in Cebu, more than half are living in the tri-cities (i.e., Cebu City, Lapu-Lapu City, and Mandaue City). These are the students living nearest to the university where the proposed academic degree program will be offered.

3.2. Research instrument

The instrument used to perform the survey had three parts. The first part is assigned for the informed consent that indicated the research purpose and background, procedures, risks and discomfort, confidentiality, and benefits. The statements in this part of the instrument were subject to students’ perusal and approval. The second part elicited students’ profiles in terms of sex, grade level, type of secondary school where enrolled, track enrolled, and area of residence in the province of Cebu. The third and final part was the scale intended to elicit the factors that could influence SHS students’ intention to enroll in BS Biology at CTU. Using Chapman’s (1981) Model of Student College Choice and further literature review, seven constructs were determined to influence intention to enroll in the proposed academic degree program. These constructs are (1) student characteristics, (2) influence of significant people, (3) marketing factor, (4) fixed university characteristics, (5) university image, (6) perceived program quality, and (7) perceived career opportunities. These constructs were operationalized through conducting a dedicated literature review to develop the items. Table 2 presents the constructs of the scale and the items assigned in each construct together with the sources as to which these items are anchored on. Each construct has unequal number of items assigned ranging from three (i.e., intention to enroll) to ten (i.e., university image). All items were measured on a five-point Likert scale with 1 as strongly disagree, 2 as disagree, 3 as neutral, 4 as agree, and 5 as strongly agree.

Table 2. Constructs of the scale with the items assigned and their corresponding references

Constructs	Item code and statement	Number of items	References
University Image [UI] The university …	[UI1] has high quality premises (i.e., vision, mission, and goals) [UI2] provides high quality education and training. [UI3] is known for its esteemed research records. [UI4] is committed to community extension activities. [UI5] is known for its internationalization of science curricular programs. [UI6] has reputable rank against other nearby HEIs. [UI7] offers a good quality of student’s life. [UI8] is known for its employable graduates. [UI9] receives international recognition. [UI10] produces graduates who aced licensure examinations.	10	Gaspar & Soares (2021); Gutiérrez-Villar et al. (2022); Krzysztof & Bogdan (2020); Snelling & Boruch (1970)
Perceived Program Quality [PPQ] The undergraduate degree program …	[PPQ1] has academic reputation. [PPQ2] is academically competitive as compared to other programs. [PPQ3] has an opportunity to major in area of interest. [PPQ4] has available tutoring services. [PPQ5] has available academic advisory services. [PPQ6] provides opportunity to travel abroad while pursuing the degree.	6	Abubakar (2017); Aldosary & Assaf (1996)
Perceived Career Opportunities [PCO] If I finish the degree program, I will have	[PCO1] the opportunity to get a job. [PCO2] a decent salary. [PCO3] a prestigious job. [PCO4] an opportunity to work abroad. [PCO5] intellectual development. [PCO6] improve my life situation.	6	Abubakar (2017); Aldosary & Assaf (1996); Gaspar & Soares (2021)
Individual Factor
Student Characteristics [SC] In this degree program,	[SC1] I know its career progression. [SC2] I am interested. [SC3] I have the academic ability to thrive. [SC4] I have the socio-economic status that fits the financial requirements.	4	Abubakar(2017); Aldosary & Assaf(1996); Chapman(1981)
External Factors
Influence of Significant People [ISP] I received advise to pursue this undergraduate degree program from …	[ISP1] faculty lecturers teaching in the same institution. [ISP2] my friends. [ISP3] my parents. [ISP4] my SHS career guidance counselor. [ISP5] my science teacher.	5	Abubakar(2017); Aldosary & Assaf(1996); Chapman(1981); Gaspar & Soares(2021); Snelling & Boruch(1970)
Marketing Factor [MF] The university invites prospect students to pursue the undergraduate degree program by	[MF1] sending mails. [MF2] hosting advertisements in different social media platforms. [MF3] joining university fairs. [MF4] organizing campus visits. [MF5] hosting career fairs.	5	Abubakar(2017); Chapman(1981); Gaspar & Soares(2021)
Fixed University Characteristics [FUC] The university …	[FUC1] offers reasonable tuition fees. [FUC2] has close proximity to our house. [FUC3] has impressive science facilities. [FUC4] has convenient admission process. [FUC5] provides scholarship opportunities. [FUC6] has low faculty to student ratio. [FUC7] maintains a safe and clean learning environment. [FUC8] has a collection of vast learning resources.	8	Abubakar(2017); Gaspar & Soares(2021); Snelling & Boruch(1970)
Intention to Enroll [IE]	[IE1] I am interested to pursuing an undergraduate degree program in Biology. [IE2] I like to know in-depth information about BS Biology. [IE3] I plan to enroll BS Biology in the future.	3	Solikhah et al.(2016)

3.3. Data gathering procedure

The researchers created a Google Form to administer a web-based survey. Then, the link of the survey form was sent via email and different social media or messaging platforms from October 2022 until January 2023. This is the same duration when the form was open and accepting responses. The survey form was ensured to accept only one response per email or student by setting Google Form to limit the user to submit one response. The researchers also ensured observance of following ethical guidelines. First, the informed consent form was discussed and retrieved from the students before participating in the survey. As evidence of their consent, the students were asked to sign the form as proof of their understanding and approval to participate in the survey. The section in which the students indicate their signature reflects the following statement: “I have read this form and decided that I will be participating in the study as described above. Its general purposes, the particulars of involvement, possible risks, and benefits have been explained to my satisfaction. I understand that I can withdraw at any time. I have received a copy of this form.” For students aged below 18 years, their parents were approached for consent and these students were given the assent form to indicate their signature as evidence of their written consent in participating the survey. The collected data from the participation of these students in the survey were exclusively used for research purpose only.

3.4. Data analysis

The statistical packages for social sciences (SPSS 22.0) and AMOS 22.0 were used to perform the analyses. Descriptive statistics such as frequencies and percentages were used to express categorical data, while means and standard deviations were used to express numerical data. Then, the psychometric properties of the scale were established. The confirmatory factor analysis (CFA) was performed to assess the convergent validity, internal consistency, and dimensionality of the developed scale. In addition, discriminant validity was investigated utilizing Pearson’s correlation coefficients and squared average variance extracted. Finally, a structural equation modelling (SEM) was done to determine the association of variables or constructs or to investigate the acceptance or rejection of the proposed hypotheses, using 0.05 level of significance as the reference value.

4. Results

4.1. Psychometric properties of the scale

The confirmatory factor analysis was performed using maximum likelihood method because of its asymptomatic efficiency outcomes for studies involving large sample sizes (Bollen, 1989; Tarima & Flournoy, 2019). First, t-values and standardized factor loading (SFL) of each item in the scale were examined to justify the analysis of the overall model data fit of the scale. The observed t-values and SFLs, respectively, range between 9.59 (FUC6) and 24.078 (MF3) and between 0.513 (FUC6) and 0.881 (MF5). While all t-values reached the cut-off value of ≥1.96, evidently, eight items have SFLs that did not meet the threshold value of ≥0.7 per Hair et al. (2014) and Kline (2016) recommendations. However, none of the items were removed, practically, for two reasons. Some studies retain items with SFLs at least 0.37 (Goni et al., 2020) or 0.41 (Ozturk, 2011). In the case of the present study, as shown in Table 4, the minimum SFL is 0.513 for item FUC6 which is relatively higher as compared to the aforecited studies. The researchers also contend that these items are conceptually important and the remaining items within the construct could not represent them if they are removed. In this regard, it may be safe to proceed analyzing the overall model data fit of the scale. There were five goodness-of-fit indices evaluated to examine the overall model fit of the CFA results. These are reflected in Table 3 along with the proposed acceptable threshold values of the researchers and the resulting values from the test. The review of these threshold value per GFI was adopted from studies of Cortes et al. (2021), Toring et al. (2022), and Toring et al. (2022). In conclusion, all five fit indices suggest an acceptable fit of the scale.

Table 3. Model data fit indices results

Model fit indices	Proposed threshold value	Source	Resulting value
CFI	>0.80	Garson(2006)	0.880
TLI	>0.85	Sharma et al.(2005)	0.871
RMSEA	<0.08	Kenny et al.(2014)	0.062
SRMR	≤0.08	Hu & Betler(1999)	0.054
Chi-square/df ratio	<3.00	Hair et al.(2009)	2.620

Eventually, the convergent validity and internal consistency of the scale were sought by using the SFLs and composite reliability (CR). The recommended minimum value for both SFL and CR is ≥0.7 (Gefen et al., 2000; Hair et al., 2014). However, as discussed earlier and as shown in Table 4, eight items have SFLs below the minimum criterion; hence, CR is used instead as evidence of convergent validity. The resulting CR values range from 0.848 to 0.929, thus, convergent validity is established and these same results proved the internal consistency of the scale. Finally, the discriminant validity was examined of which the squared AVE of a given construct should be greater than the correlation of the construct with other domains to ensure that it is statistically unique. Table 5 shows the results of discriminant validity analysis of which the squared AVE of all constructs are consistently greater than any correlation coefficients above them.

Table 4. Convergent and internal consistency results of the scale

Constructs	Item	Standardized factor loading	Average variance extracted	Composite reliability
University Image	UI1	0.725	0.565	0.929
	UI2	0.726
	UI3	0.745
	UI4	0.727
	UI5	0.751
	UI6	0.765
	UI7	0.772
	UI8	0.760
	UI9	0.771
	UI10	0.775
Perceived Program Quality	PPQ1	0.748	0.556	0.882
	PPQ2	0.756
	PPQ3	0.757
	PPQ4	0.702
	PPQ5	0.803
	PPQ6	0.701
Perceived Career Opportunities	PCO1	0.782	0.628	0.910
	PCO2	0.806
	PCO3	0.828
	PCO4	0.781
	PCO5	0.775
	PCO6	0.783
Student Characteristics	SC1	0.781	0.582	0.848
	SC2	0.810
	SC3	0.758
	SC4	0.699
Influence of Significant People	ISP1	0.773	0.623	0.892
	ISP2	0.800
	ISP3	0.801
	ISP4	0.838
	ISP5	0.730
Marketing Factor	MF1	0.672	0.634	0.895
	MF2	0.675
	MF3	0.870
	MF4	0.854
	MF5	0.881
Fixed University Characteristics	FUC1	0.657	0.498	0.886
	FUC2	0.553
	FUC3	0.807
	FUC4	0.849
	FUC5	0.689
	FUC6	0.513
	FUC7	0.688
	FUC8	0.816
Intention to Enroll	IE1	0.874	0.720	0.885
	IE2	0.832
	IE3	0.839

Table 5. Discriminant validity results

Variable	UI	PPQ	PCO	SC	ISP	MF	FUC	IE
UI	1.000
PPQ	0.717**	1.000
PCO	0.537**	0.622**	1.000
SC	0.511**	0.617**	.594**	1.000
ISP	0.424**	0.524**	0.474**	0.685**	1.000
MF	0.527**	0.600**	0.470**	0.588**	0.601**	1.000
FUC	0.570**	0.624**	.565**	0.611**	0.585**	0.662**	1.000
IE	0.322**	0.386**	0.375**	0.574**	0.521**	0.405**	0.413**	1.000
AVE	0.565	0.556	0.628	0.582	0.623	0.634	0.498	0.720
√AVE	0.752	0.746	0.793	0.763	0.789	0.796	0.706	0.849
Mean	4.120*	4.030*	4.280**	3.940*	3.790*	3.920*	4.000*	3.670*
SD	0.570	0.580	0.590	0.700	0.770	0.640	0.560	0.870

Note for mean. 1.00–1.80 = Strongly Disagree; 1.81–2.60 = Agree; 2.61–3.40 = Neutral; 3.41–4.20 = Agree*; 4.21–5.00 = Strongly Agree**

4.2. Structural model and hypotheses testing

A structural equation modelling technique was performed to examine the validity of the proposed model and research hypotheses. Using the same reference values of GFIs for CFA, the model possessed adequate goodness-of-fit with values for CFI = 0.860, TLI = 0.851, RMSEA = 0.060, and CMIN/df = 2.865. The SRMR may result in 0.091, but Hu and Betler (1999) suggest that it is acceptable provided the RMSEA is ≤0.06 which is true in the present study. Subsequently, the testing of the proposed hypotheses can proceed. As shown in Table 6, five hypotheses are supported, and the remaining six hypotheses are rejected. In particular, the influence of significant people is a significant predictor of students’ perception of university image (β_H2 = 0.566, t = 9.534, p = 0.000 < .001), program quality (β_H3 = 0.378, t = 7.587, p = 0.000 < .001), and career opportunities of the academic degree program (β_H4 = 0.639, t = 10.814, p = 0.000 < .001). A 32% of the variation in university image, 72% of the variation in perceived program quality, and 41% of the variation in perceived career opportunities is explained by the influence of significant people. University image contributes in the 72% variation in the perceived program quality because it is a significant predictor (β_H8 = 0.575, t = 10.202, p = 0.000 < .001). However, influence of significant people is not a significant predictor of students’ intention to enroll BS in Biology (β_H5 = 0.181, t = 1.219, p = 0.223 > .05). Additionally, marketing factor or strategy (β_H6 = −0.008, t = −0.105, p = 0.917 > .05), fixed university characteristics (β_H7 = −0.008, t = −0.750, p = 0.454 > .05), university image (β_H9 = 0.016, t = 0.204, p = 0.838 > .05), perceived program quality (β_H10 = −0.075, t = −0.759, p = 0.448 > .05), and perceived career opportunities (β_H11 = −0.024, t = −0.393, p = 0.694 > .05) are not predictors of intention to enroll. Only student characteristics is the predictor of students’ enrollment to the academic degree program (β_H1 = 0.622, t = 5.277, p = 0.000 > .001) and it explains 47% of the variation in the intention to enroll.

Table 6. Structural model estimates

Hypothesized path		Standardized beta	T value	p-value	Decision
H1	Intention to Enroll←Student Characteristics	0.622	5.277	***	Supported
H2	University Image←Influence of Significant People	0. 566	9.534	***	Supported
H3	Perceived Program Quality←Influence of Significant People	0.378	7.587	***	Supported
H4	Perceived Career Opportunities←Influence of Significant People	0.639	10.814	***	Supported
H5	Intention to Enroll←Influence of Significant People	0.181	1.219	0.223	Rejected
H6	Intention to Enroll←Marketing Factor	−0.008	−0.105	0.917	Rejected
H7	Intention to Enroll←Fixed University Characteristics	−0.008	−0.750	0.454	Rejected
H8	Perceived Program Quality←University Image	0.575	10.202	***	Supported
H9	Intention to Enroll←University Image	0.016	0.204	0.838	Rejected
H10	Intention to Enroll←Perceived Program Quality	−0.075	−0.759	0.448	Rejected
H11	Intention to Enroll←Perceived Career Opportunities	−0.024	−0.393	0.694	Rejected

Statistical Significance. * p<0.05, ** p<0.01, *** p<0.001, n.s. non-significant

4.3. Feasibility of students enrollment to the proposed BS Biology

While this study focuses on identifying the factors influencing students’ intention to enroll in the proposed academic degree program, it also sought to determine the chances that students will enroll in it. The distribution of students when grouped according to their intention to enroll in BS Biology is shown in Figure 2. The researchers calculated the mean score of each student under intention to enroll construct and classify their level of agreement. Following the classification scheme in Table 5 for five-point Likert scale, 59% (n = 245.44) have mean responses between strongly agree to agree. These students may have the chance to pursue the academic degree program in CTU. Meanwhile, 32% (n = 133.12) are undecided, while the remaining 9% (n = 37.44%) are certain of not enrolling to BS Biology.

Figure 2. Distribution of students according to their intention to enroll in BS Biology at CTU (n = 416).

5. Discussion

As HEIs and academic degree programs compete with one another in attracting students to enroll, a guiding model or framework reflecting the potential factors influencing students’ intention to enroll may help them how to ace the competition. In the present study, the researchers sought to develop this guiding framework and eventually examined the proposed association of constructs in the framework through a structural equation modeling approach.

However, based on the structural model and in the case of the HEI and academic degree program being studied, only the association of student characteristics with their intention to enroll in the proposed academic degree program is supported. The other seven factors linked to the endogenous variable are rejected. This single positive and significant association indicates that students with high SES, advanced academic ability, and loftier educational aspirations are generally more likely to major in STEM fields in college which the study of Biology belongs. On the contrary, those students with different characteristics pursue an opposite course or career path. These claims can be supported by the findings of previous studies indicating socio-economic status (Declercq & Verboven, 2015; Misran et al., 2012), aptitude (Rudasill & Callahan, 2010), and educational aspiration (Lichtenberger & George-Jackson, 2013) as factors affecting the preference of students in selecting their college course.

Further, as a sole predictor of students’ intention to enroll in BS Biology, this study suggests that students decide the academic degree program they will pursue on their own, and taking into account their economic condition, aptitude, and educational aspiration. In other words, the predictor variables added as a product of the literature review, such as university image proposed by Gołata and Sojkin (2020), Wilkins & Huisman (2014), and Azoury et al. (2014), perceived program quality proposed by Ozis et al. (2018) and Sari et al. (2018), and perceived program opportunities proposed by Akosah-Twumasi et al. (2018), Ahmed et al., (2017), and Nyamwange (2016), and those originally indicated in Chapman’s (1981) model (i.e., influence of significant people, marketing factor, and fixed university characteristics) do not in any way influence students’ intention of enrolling in BS Biology. However, these results do not intend to invalidate the proposed model because different results may be observed if the model is used in other contexts (e.g., other academic degree programs, HEI, or type of students). This means that, in different contexts, some of the proposed predictor variables may significantly and positively influence the endogenous variable of interest. Hence, the lack of associations of the other six exogenous variables with the endogenous variable call for further research in contexts such as those mentioned above.

Interestingly, the influence of significant people may not be a predictor of students’ intention to enroll in BS Biology, but it is seemingly an important predictor variable for their perception of the university image, perceived program quality, and perceived career opportunities. This validates the critical role of interpersonal factors or the influence of family, teachers, guidance counselors, peers, and anyone with personal affinity in guiding students about the HEI and academic degree program to enroll in and the career path to take as established in previous studies (Abe & Chikoko, 2020; Kayani et al., 2022; Kumar, 2016; Marinas et al., 2016). As they take these critical roles toward the prospective students, the findings of this study may suggest that these people need to be included in information campaign efforts of the university to promote its image and the academic degree program they intend to offer.

6. Conclusion

Although six of the predictor variables failed to influence the endogenous variable, one of the factors indicated in Chapman’s (1981) Student College Choice Model is proven useful for understanding students’ intention to enroll in BS Biology which is student characteristics. Interestingly, as influence of significant people is a predictor variable to students’ perception of university image, program quality, and career opportunities, this can be taken advantage by the HEI which will offer the proposed academic degree program to influence prospective SHS students to enroll in BS Biology. Irrespective of the disassociation of six exogenous variables to the endogenous variable, the offering of the proposed academic degree program is deemed feasible. Taking into account the mean score of individual student in the intention to enroll construct, 59% of them expressed a positive response. To increase the number of students who will express enrollment and the number of factors influencing the students’ intention to enroll in BS Biology, some implications are suggested.

6.1. Managerial implication

The rejection of six hypotheses does not literally reflect the characteristics, reputation, and program quality of the university as these are taken from the perspective of the students. Nonetheless, this may speak of its communication or marketing efforts towards its stakeholders. The results of the survey imply that they are not aware of what the university is currently working and what its efforts have led the institution to become. In this regard, it is suggested to improve the university communication efforts to these stakeholders about its success and efforts by means of effective marketing strategies or information drive campaigns.

6.2. Theoretical implication

The present study modifies and adopts Chapman’s (1981) Model of Student College Choice to respectively suit with the research aim and to adopt realistic factors that could potentially be antecedents of students’ intention to BS Biology. As the findings indicate, not all factors may influence the endogenous variable but it suggests adding unexamined variables not included here but are suggested in the literature. In other words, the model is suggested to be extended. Also, the factors can be examined for potential association as supported by the literature (e.g., marketing factor to university image, perceived program quality, and career opportunities). Finally, the model may be adopted when evaluating the factors influencing students’ intention to enroll in other academic degree programs and even in other HEIs.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.