Admission Requirements and Academic Performance of Board vs Non-Board Course in Higher Education Institution
Abstract
Higher Education Institutions require specific admission criteria to select the best candidates for a particular program. This study aims to assess the admission requirements and academic performance of the board and non-board course learners. Specifically, this quantitative study utilized a descriptive-correlational research design. The data came from randomly selected third-year college students in the different Board and Non-Board programs enrolled in the academic year 2020-2021. There were 286 respondents who took part in the study, 153 from the board course program, Bachelor of Science in Elementary Education, and 133 from the non-board course program, Bachelor of Science in Information Technology. The data revealed that the most number of enrollees in the non-board course, BSIT is from the Technical-Vocational-Livelihood (TVL) Strand, while most learners from the Board course, BSEE belong to the General Academic Strand (GAS). Further, findings showed that the High-school Grade Point Average and the College Academic Performance of students from the non-board course, BSIT, were moderately correlated, and a similar relationship is observed for the variables College Admission Test and GPA. Meanwhile, for the Board Course, BSEE, admission tests, and high-school GPA are predictors of college academic performance. On the other hand, high-school strands are not predictors of the BSEE student's GPA. In conclusion, the College admission tests and high-school GPA are essential admission requirements for the board and non-board programs to predict academic performance. However, the high-school strand can be a determining factor for the academic performance for the non-board course, but not for the board course.
Keywords:
Admission Requirements, Academic Performance, Strand, Board and Non-Board Course
References
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Turkish Journal of Computer and Mathematics Education, 12(13), 3560-
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Kurz, A., Talapatra, D., & Roach, A.T. (2012). Meeting the curricular137
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strand matter in nursing students’ academic self-regulated learning
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cfm?abstract_id=3802973.
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Conference on Emerging Technologies 2019, Daejeon, South Korea,
unpublished.
Magbag, A., & Raga, R. (2019). Prediction of college academic performance of senior high school graduates using classification techniques. International Journal of Scientific & Technology Research, 9, 04.
Magdadaro, L. R. P. (2020). Passion-based vs. practical-based preference of strand in senior high school. International Journal of Academic Research in
Business and Social Sciences, 10(3).https://doi.org/10.6007/ijarbss/
v10-i3/7031.
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Mcdonald, D. R. (2000). Prediction models for performance on the elementary and three methods of predicting first-year grades. Research in Higher Education, 43, 187-207.
McIntosh, J., & Munk, M.D. (2007). Scholastic ability vs family background
in educational success: Evidence from Danish sample survey data. Journal of
Population Economics, 20, 101–120. http://vbn.aau.dk/da/publications/
scholastic-ability-vs-familybackground-in-educational-successevidence-from-danish-sample-surveydata(2c5d8080-7d04-11de-9240-
000ea68e967b)/export.html
Mufti, T. S., & Qayum, I. (2014).Rehman Medical College admission
criteria as an indicator of students’ performance in university professional examinations. Journal of Ayub Medical College, Abbottabad: JAMC, 26(4), 564-567.
Noble, J. (2003). The effect of using ACT composite score and high school
average on college admission decisions for racial/ethnic groups (ACT Research Report RR2003-1). ACT Inc.
O’Connor, M. C., & Paunonen, S. V. (2007). Big five personality predictors of postsecondary academic performance. Personality and Individual Differences,43(5), 971–990. https://doi.org/10.1016/j.paid.2007.03.017.
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officialgazette.gov.ph/k12/#section-7.
Patterson, F., Knight, A., Dowell, J., Nicholson, S., Cousans, F., & Cleland, J. (2016). How effective are selection methods in medical education? A systematic review. Med Educ.,50(1):36–60.
Pike, G. R., & Saupe, J. L. (2002). Doeshigh school matter? An analysis of three methods of predicting first-year grades. Research in Higher Education,43, 187-207.
Rajandran, K., Hee, T., Kanawarthy, S., Soon, L., Kamaludin, H., &
Khezrimotlagh, D. (2014). Factors affecting first year undergraduate
students’ academic performance.
Republic of the Philippines OFFICE OF THE PRESIDENT. (n.d.). https://ched.
gov.ph/wp-content/uploads/2018/01/ CMO-No.-105-s.-2017-Policy-on theAdmission-of-Senior-High-SchoolGraduates-to-the-Higher-EducationInstitutions-Effective-AcademicYear-2018-2019.pdf
Reynolds, A. J., & Walberg, H. J. (1992). A structural model of science
achievement and attitude: An extension to high school. Journal of Educational Psychology, 84(3), 371–382. https://doi.
org/10.1037/0022-0663.84.3.371
Rigney, T.J. (2003). A study on the relationship between entry
qualifications and achievement of third level business studies students. The Irish Journal of Management, 117-138
Sawyer, R. K. (2010). Learning for creativity. In R. A. Beghetto &
J. C. Kaufman (Eds.), Nurturing creativity in the classroom (pp.
172–190). Cambridge University Press. https://doi.org/10.1017/
CBO9780511781629.009
Smithers, S. Catano, V. & Cunningham, D. (2004). What predicts performance in Canadian dentals schools? Journal of Dental Education, 68 (6), 598-613.
Sulphey, M. M., Al-Kahtani, N.S. & Syed, A.M. (2018). Relationship between admission grades and academic achievement. Entrepreneurship and Sustainability Issues, Entrepreneurship and Sustainability Center. 5(3), pp.648 -
Tiffin, P.A., Mwandigha, L.M., Paton, L.W. et al. (2016). Predictive validity of the UKCAT for medical school undergraduate performance: a national prospective cohort study. BMC Med 14, 140 (2016). https://doi.org/10.1186/s12916-016-0682-7.
Valli, Jayanthi, S., Balakrishnan, S., Lim Siok Ching, A., Aaqilah Abdul Latiff,N., & Nasirudeen, A. M. A. (2014).Factors contributing to academic performance of students in a tertiary institution in Singapore. American
Journal of Educational Research, 2(9), 752–758. https://doi.org/10.12691/
education-2-9-8.
Yousafzai, I. I., & Jamil, B. (2019).Relationship between admission
criteria and academic performance: A correlational study in nursing
students. Pakistan Journal of Medical Sciences, 35(3), 858–861. https://doi.org/10.12669/pjms.35.3.217
Zwick, R., & Sklar, J. C. (2005). Predicting college grades and degree completion using high school grades and SAT Scores: The role of student ethnicity and first language.American Educational Research Journal, 42(3), 439–464. https://doi.org/10.3102/00028312042003439
Asian Development Bank and Department of Education of the Government of the Philippines. (2019). Youth education investment and labor market outcomes
in the Philippines: Survey report.Manila. https://development.asia/
insight/factors-affecting-senior-highschool-track-offerings-Philippines
Basri, W. S., Alandejani, J. A., & Almadani, F. M. (2018b). ICT adoption impact on students’ academic performance:Evidence from Saudi universities.
Education Research International, 1–9.https://doi.org/10.1155/2018/1240197.
Bridgeman, B., Pollack, J., & Burton, N.(2008). Predicting grades in differenttypes of college courses. Ets Research Report Series, 1, i–27. https://doi.org/10.1002/j.2333-8504.2008.tb02092.x
Briggs, D. C., & Weeks, J. P. (2009). The impact of vertical scaling decisions on growth interpretations. Educational Measurement: Issues and Practice,28(4), 3–14. https://doi.org/10.1111/j.1745-3992.2009.00158.x
Brillantes, K. B., Orbeta, A. C., FranciscoAbrigo, K. A., Capones, E. M., &
Jovellanos, J. B. (2019). Status of senior high school implementation: A
process evaluation. https://pidswebs. pids.gov.ph/CDN/PUBLICATIONS/
pidsdps1913.pdf
Brillantes, K. B., Orbeta, A. C., FranciscoAbrigo, K. A., Capones, E. M., &
Jovellanos, J. B. (2019). Status of senior high school implementation: A
process evaluation. https://pidswebs.pids.gov.ph/CDN/PUBLICATIONS/
pidsdps1913.pdf
Canque M., Derasin L., & Pinatil L .(2021). Senior high school background
and GPA of the education students in a state university in the Philippines.
Turkish Journal of Computer and Mathematics Education, 12(13), 3560-
3566.
De Visser, M., Fluit, C., Cohen-Schotanus, J., & Laan, R. (2018). The effects of a non-cognitive versus cognitive admission procedure within cohorts in one medical school. Adv Health Sci Educ Theory Pract., 23(1):187–200.
Engadin, C. (2019). Accountancy, business and management (ABM) strand.
Edukasyon.ph. Retrieved on July 23,2019 from https://www.edukasyon.ph/
courses/senior-high-tracks/academicbusiness-and-management-strand
Evans, V. (2012). Cognitive linguistics.WIREs Cognitive Science, 3(2), 129–
141. https://doi.org/10.1002/wcs.1163
Feldman, D. C. (2005). The food’s no good and they don’t give us enough:
Reflections on Mintzberg’s critique of MBA education. Academy of
Management Learning & Education,4(2), 217–220.
Feldman, D. C. (2005). The food’s no good and they don’t give us enough:
Reflections on Mintzberg’s critique of MBA education. Academy of
Management Learning & Education,4(2), 217–220.
Garton, B., Dyer, James, and King, B.(2000) The use of learning styles
and admission crtieria in predicting academic performance and retention
of college freshmen. Journal of Agricultural Education. 41.10.5032/jae.
2000.02046.
Geiser, S., & Santelices, M. V. (2007). Validity of high-school grades in
predicting student success beyond the freshman year: High-school record
vs. standardized tests as indicators of four-year college outcomes. Research & Occasional Paper Series. http://files. eric.ed.gov/fulltext/ED502858.pdf
Golding, P., & Donaldson, O. (2006).Predicting academic performance.
Frontiers in Education Conference, 36th Annual, 21-26. doi:10.1109/
FIE.2006.322661
Gomez, F. E. (2017, August). Predicting academic performance: A ... - SFA
scholarworks. https://scholarworks.sfasu.edu/cgi/viewcontent. cgi?article=1076&context=etds.
Harackiewicz, J. M., Tauer, J. M., Barron, K. E., Elliot, A. J. (2002). Predicting success in college: A longitudinal study of achievement goals and ability measures as predictors of interest and performance from freshman year through 97 graduation. Journal of Educational Psychology, 94, 562-575.doi:10.1037//0022-0663.94.3.562
Johnston, C. G. (2006). Predictors of college success among African
American, Caucasian, and Hispanic students. Dissertation. Texas Tech
University.
Kagan, S., Carroll, J., Comer, J., & ScottLittle, C. (2006). Alignment: A missing link in early childhood transitions? Young Children. 61
Kelly, M.E., Patterson, F., O’Flynn, S., Mulligan, J., & Murphy, A.W. (2018).A systematic review of stakeholder views of selection methods for medical schools admission. BMC Med Educ.,18(1),139.
Kurz, A., Talapatra, D., & Roach, A.T. (2012). Meeting the curricular137
challenges of inclusive assessment: The role of alignment, opportunity to learn, and student engagement. International Journal of Disability, Development and Education, 59(1), 37–52. https://doi.org /10.1080/1034912x.2012.654946
Liu, X., & Lee, L. F. (2010). GMM estimation of social interaction
models with centrality. Journal of Econometrics, 159(1), 99–115. https://
doi.org/10.1016/j.jeconom.2010.04.009.
Malaga, X., & Oducado, R. M. (2021, March 22). Does senior high school
strand matter in nursing students’ academic self-regulated learning
and academic performance? SSRN.https://papers.ssrn.com/sol3/papers.
cfm?abstract_id=3802973.
Magbag, A., & Raga, R. (2019). Prediction of college academic performance of senior high school graduates using machine learning, Proc. International
Conference on Emerging Technologies 2019, Daejeon, South Korea,
unpublished.
Magbag, A., & Raga, R. (2019). Prediction of college academic performance of senior high school graduates using classification techniques. International Journal of Scientific & Technology Research, 9, 04.
Magdadaro, L. R. P. (2020). Passion-based vs. practical-based preference of strand in senior high school. International Journal of Academic Research in
Business and Social Sciences, 10(3).https://doi.org/10.6007/ijarbss/
v10-i3/7031.
Mascolo, J. T., Alfonso, V. C., & Flanagan, D. P. (2014). Essentials of planning, selecting, and tailoring interventions for unique learners. John Wiley & Sons.
Mcdonald, D. R. (2000). Prediction models for performance on the elementary and three methods of predicting first-year grades. Research in Higher Education, 43, 187-207.
McIntosh, J., & Munk, M.D. (2007). Scholastic ability vs family background
in educational success: Evidence from Danish sample survey data. Journal of
Population Economics, 20, 101–120. http://vbn.aau.dk/da/publications/
scholastic-ability-vs-familybackground-in-educational-successevidence-from-danish-sample-surveydata(2c5d8080-7d04-11de-9240-
000ea68e967b)/export.html
Mufti, T. S., & Qayum, I. (2014).Rehman Medical College admission
criteria as an indicator of students’ performance in university professional examinations. Journal of Ayub Medical College, Abbottabad: JAMC, 26(4), 564-567.
Noble, J. (2003). The effect of using ACT composite score and high school
average on college admission decisions for racial/ethnic groups (ACT Research Report RR2003-1). ACT Inc.
O’Connor, M. C., & Paunonen, S. V. (2007). Big five personality predictors of postsecondary academic performance. Personality and Individual Differences,43(5), 971–990. https://doi.org/10.1016/j.paid.2007.03.017.
Official Gazette. (n.d.). The K-12 Basic Education Program. https://www.
officialgazette.gov.ph/k12/#section-7.
Patterson, F., Knight, A., Dowell, J., Nicholson, S., Cousans, F., & Cleland, J. (2016). How effective are selection methods in medical education? A systematic review. Med Educ.,50(1):36–60.
Pike, G. R., & Saupe, J. L. (2002). Doeshigh school matter? An analysis of three methods of predicting first-year grades. Research in Higher Education,43, 187-207.
Rajandran, K., Hee, T., Kanawarthy, S., Soon, L., Kamaludin, H., &
Khezrimotlagh, D. (2014). Factors affecting first year undergraduate
students’ academic performance.
Republic of the Philippines OFFICE OF THE PRESIDENT. (n.d.). https://ched.
gov.ph/wp-content/uploads/2018/01/ CMO-No.-105-s.-2017-Policy-on theAdmission-of-Senior-High-SchoolGraduates-to-the-Higher-EducationInstitutions-Effective-AcademicYear-2018-2019.pdf
Reynolds, A. J., & Walberg, H. J. (1992). A structural model of science
achievement and attitude: An extension to high school. Journal of Educational Psychology, 84(3), 371–382. https://doi.
org/10.1037/0022-0663.84.3.371
Rigney, T.J. (2003). A study on the relationship between entry
qualifications and achievement of third level business studies students. The Irish Journal of Management, 117-138
Sawyer, R. K. (2010). Learning for creativity. In R. A. Beghetto &
J. C. Kaufman (Eds.), Nurturing creativity in the classroom (pp.
172–190). Cambridge University Press. https://doi.org/10.1017/
CBO9780511781629.009
Smithers, S. Catano, V. & Cunningham, D. (2004). What predicts performance in Canadian dentals schools? Journal of Dental Education, 68 (6), 598-613.
Sulphey, M. M., Al-Kahtani, N.S. & Syed, A.M. (2018). Relationship between admission grades and academic achievement. Entrepreneurship and Sustainability Issues, Entrepreneurship and Sustainability Center. 5(3), pp.648 -
Tiffin, P.A., Mwandigha, L.M., Paton, L.W. et al. (2016). Predictive validity of the UKCAT for medical school undergraduate performance: a national prospective cohort study. BMC Med 14, 140 (2016). https://doi.org/10.1186/s12916-016-0682-7.
Valli, Jayanthi, S., Balakrishnan, S., Lim Siok Ching, A., Aaqilah Abdul Latiff,N., & Nasirudeen, A. M. A. (2014).Factors contributing to academic performance of students in a tertiary institution in Singapore. American
Journal of Educational Research, 2(9), 752–758. https://doi.org/10.12691/
education-2-9-8.
Yousafzai, I. I., & Jamil, B. (2019).Relationship between admission
criteria and academic performance: A correlational study in nursing
students. Pakistan Journal of Medical Sciences, 35(3), 858–861. https://doi.org/10.12669/pjms.35.3.217
Zwick, R., & Sklar, J. C. (2005). Predicting college grades and degree completion using high school grades and SAT Scores: The role of student ethnicity and first language.American Educational Research Journal, 42(3), 439–464. https://doi.org/10.3102/00028312042003439
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2022-12-13
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