Admission Requirements and Academic Performance of Board vs Non-Board Course in Higher Education Institution
Keywords:
Admission Requirements, Academic Performance, Strand, Board and Non-Board Course
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.References
Alamoudi, A. A., Fallatah, H. I., Eldakhakhny, B. M., Kamel, F. O., AlShawwa, L. A., & Elsamanoudy, A. Z. (2021). Relationship between admission criteria and academic performance in basic science courses in health science colleges in KAU. BMC Medical Education, 21(1). https://doi.org/10.1186/s12909-021-02502-4
Alipio, M. (2020). Academic Adjustment and Performance among Filipino Freshmen College Students in the Health Sciences: Does Senior High School Strand Matter? Academic Adjustment and Performance among Filipino Freshmen College Students in the Health Sciences: Does Senior High School Strand Matter? https://doi.org/10.35542/osf.io/xq4pk
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. Retrieved from https://development.asia/insight/factors-affecting-senior-high-school-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, 2018, 1–9. https://doi.org/10.1155/2018/1240197
Bridgeman, B., Pollack, J., & Burton, N. (2008). Predicting Grades In Different Types Of College Courses. Ets Research Report Series, 2008(1), i–27. https://doi.org/10.1002/j.2333-8504.2008.tb02092.x
Brillantes, K. B., Orbeta, A. C., Francisco-Abrigo, K. A., Capones, E. M., & Jovellanos, J. B. (2019, December). Status of Senior High School Implementation: A Process Evaluation. Https://Www.Pids.Gov.Ph/. Retrieved June 7, 2021, from https://pidswebs.pids.gov.ph/CDN/PUBLICATIONS/pidsdps1913.pdf
Burton, N. W. and Ramist, L. (2001). Predicting success in college: SAT studies of classes graduating since 1980 (College Board Research Report 2001-02). New York, NY: The College Board http://mc-3241-1259741632.us-east-1.elb.amazonaws.com/sites/default/files/publications/2012/7/researchreport-2001-2-predicting-college-success-sat-studies.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
Canadian Career Development Foundation (2006). Big Picture of Career Development Theory. Retrieved from http://www.ccdf.ca/ccdf/NewCoach /english/ccoache/e4a _bp_theory.htm
Conijn, R., Snijders, C., Kleingeld, A., and Matzat, U. (2017). Predicting Student Performance from LMS Data: A Comparison of 17 Blended Courses Using Moodle LMS, IEEE Trans. on Learning Technologies, 10(1), pp. 17–29, doi:10.1109/TLT.2016.2616312.
Department of Education. (2019). Retrieved April 27, 2022, from https://www.deped.gov.ph/wp-content/uploads/2019/08/DO_s2019_021.pdf
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.
Dutt S., Krishnakumar K. (2017). Gender and Academic Achievement in Engineering Colleges, International Journal of Engineering Research & Technology (ijert). 6(6) http://dx.doi.org/10.17577/IJERTV6IS060456
D.V. Silfverberg and A.C. Orbeta. (2016). The Role of Entrance Exams in Academic Performance of Students with Low Socioeconomic Background: Evidence from the SGP-PA, Proc. 13th National Convention on Statistics.
Enhanced Basic Education Act of 2013. (n.d.). Retrieved from https://www.officialgazette.gov.ph/2013/05/15/repu blic-act-no-10533
Engadin, Corp. (2019). Accountancy, Business and Management (ABM) Strand. Edukasyon.PH. Retrieved on July 23, 2019 fromhttps://www.edukasyon.ph/courses/senior-high-tracks/academic/abm-accountancy-business-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.
Fraser, B. J., Walberg, H. J., Welch, W. W., & Hattie, J. A. (1987). Syntheses of educational productivity research. International Journal of Educational Research, 11(2), 147–252. https://doi.org/10.1016/0883-0355(87)90035-8
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. Centre for Studies in Higher Education, University of California.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. Retrieved November 5, 2021, from 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
Kagan, Sharon & Carroll, Jude & Comer, James & Scott-Little, Catherine. (2006). Alignment: A Missing Link in Early Childhood Transitions?. Young Children. 61.
Kelly ME, Patterson F, O’Flynn S, Mulligan J, Murphy AW. (2018). A systematic review of stakeholder views of selection methods for medical schools admission. BMC Med Educ. 18(1):139.
Kobrin, J. L., Patterson, B. F., Shaw, E. J., Mattern, K. D., and Barbuti, S. M. (2008). Validity of the SAT for predicting first-year college grade point average (College Board Research Report No. 2008-5). New York, NY: The College Board.
Krishnakumar, K., & Dutt, S. (2017). Predictive value of Engineering entrance test on academic performance in Engineering Degree course. International Journal of Recent Engineering Research and Development, 38-43.
Kovacic, J. Z. (2010). Early Prediction of Student Success: Mining Students Enrolment Data, Proc. 2010 InSITE Conference, pp. 647–665, doi: 10.28945/1281.
Kurz, A., Talapatra, D., & Roach, A. T. (2012). Meeting the Curricular 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. Retrieved October 31, 2021, from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3802973.
Magbag, A. and 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. and Raga, R. (2019). Prediction of College Academic Performance of Senior High School Graduates Using Classification Techniques. International Journal Of Scientific & Technology Research. Volume 9, Issue 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. Hoboken, New Jersey: John Wiley & Sons.
McIntosh, J. and 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-family-background-in-educational-success-evidence-from-danish-sample-survey-data(2c5d8080-7d04-11de-9240-000ea68e967b)/export.html
Montalbo, Y. Evangelista and M. Bernal ―Admission Test as Predictor of Student Performance in Political Science and Psychology Students of Rizal Technological University, Asia Pacific Journal of Multidisciplinary Research, 6(3), pp. 68–73, 2018.
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). Iowa City, IA: ACT Inc.
O'Connor, M. C., & Paunonen, S. V. (2007). Big Five personality predictors of post-secondary 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, Retrieved from 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). Does high school matter? An analysis of three methods of predicting first-year grades. Research in Higher Education, 43, 187-207.
Rajandran, Kanagi & Hee, Tan & Kanawarthy, Sarimila & Soon, Lim & Kamaludin, Haslina & Khezrimotlagh, Dariush. (2014). Factors Affecting First Year Undergraduate Students Academic Performance.
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
Shahiri, H. Wahidah & N. Rashid,. (2015). A Review on Predicting Student’s Performance Using Data Mining Techniques, Procedia Computer Science, pp. 414-422.
Sharf, R.S. (2006). Applying Career Development Theory to Counseling. (4th Ed.).Pacific Grove, CA: Brooks/Cole Publishing. Retrieved from https://www.careers.govt.nz/resources/career-practice/career-theory-models/parsons-theory/
Silfverberg, D.V. and Orbeta, A.C.. (2016). The Role of Entrance Exams in Academic Performance of Students with Low Socioeconomic Background: Evidence from the SGP-PA, Proc. 13th National Convention on Statistics.
Smithers, S., Catano, V., and Cunningham, D. (2004). What predicts performance in Canadian dental 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 - 658. ff10.9770/jesi.2018.5.3(17) ff. ffhal-01829634f.
Tiffin, P.A., Mwandigha, L.M., Paton, L.W. et al. 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. (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
Alipio, M. (2020). Academic Adjustment and Performance among Filipino Freshmen College Students in the Health Sciences: Does Senior High School Strand Matter? Academic Adjustment and Performance among Filipino Freshmen College Students in the Health Sciences: Does Senior High School Strand Matter? https://doi.org/10.35542/osf.io/xq4pk
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. Retrieved from https://development.asia/insight/factors-affecting-senior-high-school-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, 2018, 1–9. https://doi.org/10.1155/2018/1240197
Bridgeman, B., Pollack, J., & Burton, N. (2008). Predicting Grades In Different Types Of College Courses. Ets Research Report Series, 2008(1), i–27. https://doi.org/10.1002/j.2333-8504.2008.tb02092.x
Brillantes, K. B., Orbeta, A. C., Francisco-Abrigo, K. A., Capones, E. M., & Jovellanos, J. B. (2019, December). Status of Senior High School Implementation: A Process Evaluation. Https://Www.Pids.Gov.Ph/. Retrieved June 7, 2021, from https://pidswebs.pids.gov.ph/CDN/PUBLICATIONS/pidsdps1913.pdf
Burton, N. W. and Ramist, L. (2001). Predicting success in college: SAT studies of classes graduating since 1980 (College Board Research Report 2001-02). New York, NY: The College Board http://mc-3241-1259741632.us-east-1.elb.amazonaws.com/sites/default/files/publications/2012/7/researchreport-2001-2-predicting-college-success-sat-studies.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
Canadian Career Development Foundation (2006). Big Picture of Career Development Theory. Retrieved from http://www.ccdf.ca/ccdf/NewCoach /english/ccoache/e4a _bp_theory.htm
Conijn, R., Snijders, C., Kleingeld, A., and Matzat, U. (2017). Predicting Student Performance from LMS Data: A Comparison of 17 Blended Courses Using Moodle LMS, IEEE Trans. on Learning Technologies, 10(1), pp. 17–29, doi:10.1109/TLT.2016.2616312.
Department of Education. (2019). Retrieved April 27, 2022, from https://www.deped.gov.ph/wp-content/uploads/2019/08/DO_s2019_021.pdf
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.
Dutt S., Krishnakumar K. (2017). Gender and Academic Achievement in Engineering Colleges, International Journal of Engineering Research & Technology (ijert). 6(6) http://dx.doi.org/10.17577/IJERTV6IS060456
D.V. Silfverberg and A.C. Orbeta. (2016). The Role of Entrance Exams in Academic Performance of Students with Low Socioeconomic Background: Evidence from the SGP-PA, Proc. 13th National Convention on Statistics.
Enhanced Basic Education Act of 2013. (n.d.). Retrieved from https://www.officialgazette.gov.ph/2013/05/15/repu blic-act-no-10533
Engadin, Corp. (2019). Accountancy, Business and Management (ABM) Strand. Edukasyon.PH. Retrieved on July 23, 2019 fromhttps://www.edukasyon.ph/courses/senior-high-tracks/academic/abm-accountancy-business-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.
Fraser, B. J., Walberg, H. J., Welch, W. W., & Hattie, J. A. (1987). Syntheses of educational productivity research. International Journal of Educational Research, 11(2), 147–252. https://doi.org/10.1016/0883-0355(87)90035-8
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. Centre for Studies in Higher Education, University of California.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. Retrieved November 5, 2021, from 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
Kagan, Sharon & Carroll, Jude & Comer, James & Scott-Little, Catherine. (2006). Alignment: A Missing Link in Early Childhood Transitions?. Young Children. 61.
Kelly ME, Patterson F, O’Flynn S, Mulligan J, Murphy AW. (2018). A systematic review of stakeholder views of selection methods for medical schools admission. BMC Med Educ. 18(1):139.
Kobrin, J. L., Patterson, B. F., Shaw, E. J., Mattern, K. D., and Barbuti, S. M. (2008). Validity of the SAT for predicting first-year college grade point average (College Board Research Report No. 2008-5). New York, NY: The College Board.
Krishnakumar, K., & Dutt, S. (2017). Predictive value of Engineering entrance test on academic performance in Engineering Degree course. International Journal of Recent Engineering Research and Development, 38-43.
Kovacic, J. Z. (2010). Early Prediction of Student Success: Mining Students Enrolment Data, Proc. 2010 InSITE Conference, pp. 647–665, doi: 10.28945/1281.
Kurz, A., Talapatra, D., & Roach, A. T. (2012). Meeting the Curricular 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. Retrieved October 31, 2021, from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3802973.
Magbag, A. and 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. and Raga, R. (2019). Prediction of College Academic Performance of Senior High School Graduates Using Classification Techniques. International Journal Of Scientific & Technology Research. Volume 9, Issue 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. Hoboken, New Jersey: John Wiley & Sons.
McIntosh, J. and 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-family-background-in-educational-success-evidence-from-danish-sample-survey-data(2c5d8080-7d04-11de-9240-000ea68e967b)/export.html
Montalbo, Y. Evangelista and M. Bernal ―Admission Test as Predictor of Student Performance in Political Science and Psychology Students of Rizal Technological University, Asia Pacific Journal of Multidisciplinary Research, 6(3), pp. 68–73, 2018.
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). Iowa City, IA: ACT Inc.
O'Connor, M. C., & Paunonen, S. V. (2007). Big Five personality predictors of post-secondary 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, Retrieved from 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). Does high school matter? An analysis of three methods of predicting first-year grades. Research in Higher Education, 43, 187-207.
Rajandran, Kanagi & Hee, Tan & Kanawarthy, Sarimila & Soon, Lim & Kamaludin, Haslina & Khezrimotlagh, Dariush. (2014). Factors Affecting First Year Undergraduate Students Academic Performance.
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
Shahiri, H. Wahidah & N. Rashid,. (2015). A Review on Predicting Student’s Performance Using Data Mining Techniques, Procedia Computer Science, pp. 414-422.
Sharf, R.S. (2006). Applying Career Development Theory to Counseling. (4th Ed.).Pacific Grove, CA: Brooks/Cole Publishing. Retrieved from https://www.careers.govt.nz/resources/career-practice/career-theory-models/parsons-theory/
Silfverberg, D.V. and Orbeta, A.C.. (2016). The Role of Entrance Exams in Academic Performance of Students with Low Socioeconomic Background: Evidence from the SGP-PA, Proc. 13th National Convention on Statistics.
Smithers, S., Catano, V., and Cunningham, D. (2004). What predicts performance in Canadian dental 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 - 658. ff10.9770/jesi.2018.5.3(17) ff. ffhal-01829634f.
Tiffin, P.A., Mwandigha, L.M., Paton, L.W. et al. 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. (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
Published
2022-12-13
Section
Articles
Copyright (c) 2022 Asia Pacific Journal of Social and Behavioral Sciences
Copyright holder is the Bukidnon State University.
