University context, teachers and students: links and academic success

Authors

DOI:

https://doi.org/10.35362/rie8814733

Keywords:

academic success; university context; educational analysis; visualization techniques

Abstract

The promotion of quality education in higher education institutions promotes self-efficacy. The objective of the work was directed to the analysis of the characteristics of the faculty and the academic success of students at the end of the first year in the university context. The population studied was 6690 students and 256 professors, the data set had 15 variables between numerical and categorical. Descriptive statistics, metrics designed to evaluate meaningful data and advanced visualization techniques were used. The results revealed the essential profile of experienced and mature teachers, both in teaching and age groups. Experienced teachers who participated in teaching at a rate of more than 66%, influenced with 72% certainty the academic success of the student body. In the short term, novice teachers whose participation rate was 33% showed a positive effect. In the long term, students changed (8%) or dropped out (59%) of the university degree. The usefulness of these results provides suggestions for meaningful and timely teaching, provided that the distribution of experienced and mature faculty corresponds to two to three thirds of the total number of first-year faculty in the university degree program

Downloads

Download data is not yet available.

References

Abarca, M. S., Gómez, M. T. P. y Covarrubias, M. de L. V. (2015). Análisis de los factores que contribuyen al éxito académico en estudiantes universitarios. Revista Internacional de Educación y Aprendizaje, 3(2), 124-137.

Aleksandrova, Y. y Parusheva, S. (2019). Social media usage patterns in higher education institutions - An empirical study. International Journal of Emerging Technologies in Learning, 14(5), 108-121. https://doi.org/10.3991/ijet.v14i05.9720

Alyahyan, E. y Düştegör, D. (2020). Predicting academic success in higher education: literature review and best practices. In International Journal of Educational Technology in Higher Education, 17(1), 1-21. https://doi.org/10.1186/s41239-020-0177-7

Amida, A., Algarni, S. y Stupnisky, R. (2020). Testing the relationships of motivation, time management and career aspirations on graduate students’ academic success. Journal of Applied Research in Higher Education. https://doi.org/10.1108/JARHE-04-2020-0106

Angervall, P. (2018). The academic career: a study of subjectivity, gender and movement among women university lecturers. Gender and Education, 30(1), 105-118. https://doi.org/10.1080/09540253.2016.1184234

Araque, F., Roldán, C. y Salguero, A. (2009). Factors influencing university drop out rates. Computers and Education, 53(3), 563-574. https://doi.org/10.1016/j.compedu.2009.03.013

Boluda, I. K. y López, N. V. (2012). El docente universitario y sus efectos en el estudiante. Estudios Sobre Educacion, 23(23), 157-182. https://bit.ly/3rn0jsG

Breiman, L. (2001). Random Forests. Machine Learning, 45(1), 5-32. https://doi.org/10.1023/A:1010933404324

Brin, S., Motwani, R., Ullman, J. D. y Tsur, S. (1997). Dynamic itemset counting and implication rules for market basket data. ACM SIGMOD Record, 26(2), 255-264. https://doi.org/10.1145/253262.253325

Campbell, C. M., Smith, M., Dugan, J. P. y Komives, S. R. (2012). Mentors and college student leadership outcomes: The importance of position and process. Review of Higher Education, 35(4), 595-625. https://doi.org/10.1353/rhe.2012.0037

Campbell, H. E., Steiner, S. y Gerdes, K. (2005). Student Evaluations of Teaching: How You Teach and Who You Are. Journal of Public Affairs Education, 11(3), 211-231. https://doi.org/10.1080/15236803.2005.12001395

Chickering, A. W. y Gamson, Z. F. (1987). Seven Principles for Good Practice in Undergraduate Graduation. AAHE Bulletin;, 39(7), 3-7.

Cho, Y., Kim, M., Svinicki, M. D. y Decker, M. L. (2011). Exploring teaching concerns and characteristics of graduate teaching assistants. Teaching in Higher Education, 16(3), 267-279. https://doi.org/10.1080/13562517.2010.524920

Crisp, G., Taggart, A. y Nora, A. (2015). Undergraduate Latina/o Students: A Systematic Review of Research Identifying Factors Contributing to Academic Success Outcomes. Review of Educational Research, 85(2), 249-274. https://doi.org/10.3102/0034654314551064

Cunha, J. M., Miller, T. y Weisburst, E. (2018). Information and College Decisions: Evidence From the Texas GO Center Project. Educational Evaluation and Policy Analysis, 40(1), 151-170. https://doi.org/10.3102/0162373717739349

Darling-Hammond, L. (2000). Teacher Quality and Student Achievement. Education Policy Analysis Archives, 8(0), 1. https://doi.org/10.14507/epaa.v8n1.2000

de Boer, H., Donker, A. S. y Van der Werf, M. P. C. (2014). Effects of the Attributes of Educational Interventions on Students’ Academic Performance: A Meta-Analysis. Review of Educational Research, 84(4), 509-545. https://doi.org/10.3102/0034654314540006

Fogarty, J. L., Wang, M. C. y Creek, R. (1983). A Descriptive Study of Experienced and Novice Teachers’ Interactive Instructional Thoughts and Actions, The Journal of Educational Research, 77, 22-32. https://doi.org/10.2307/27540012

Glogowska, M., Young, P. y Lockyer, L. (2007). Should I go or should I stay? Active Learning in Higher Education, 8(1), 63-77. https://doi.org/10.1177/1469787407074115

Gutiérrez, M., Tomás, J.-M. y Alberola, S. (2018). Apoyo docente, compromiso académico y satisfacción del alumnado universitario. Estudios Sobre Educación, 35(0), 535-555. https://doi.org/10.15581/004.35.535-555

Guanin-Fajardo, J., Casillas, J. y Chiriboga-Casanova, W. (2019). Aprendizaje semi-supervisado para descubrir la escala de tiempo promedio de graduación de estudiantes universitarios. Revista Conrado, 15(70). Recuperado de https://bit.ly/3rxdnfe

Jacobi, M. (1991). Mentoring and Undergraduate Academic Success: A Literature Review. Review of Educational Research, 61(4), 505-532. https://doi.org/10.3102/00346543061004505

Jepsen, C. (2005). Teacher characteristics and student achievement: Evidence from teacher surveys. Journal of Urban Economics, 57(2), 302-319. https://doi.org/10.1016/j.jue.2004.11.001

Kara, N., Çubukçuoğlu, B. y Elçi, A. (2020). Using social media to support teaching and learning in higher education: An analysis of personal narratives. Research in Learning Technology, 28, 1-16. https://doi.org/10.25304/rlt.v28.2410

Konrad, T., Wiek, A. y Barth, M. (2021). Learning processes for interpersonal competence development in project-based sustainability courses - insights from a comparative international study. International Journal of Sustainability in Higher Education, ahead-of-p(ahead-of-print). https://doi.org/10.1108/ijshe-07-2020-0231

Korhonen, V. y Törmä, S. (2016). Engagement with a teaching career - how a group of finnish university teachers experience teacher identity and professional growth. Journal of Further and Higher Education, 40(1), 65-82. https://doi.org/10.1080/0309877X.2014.895301

Korobova, N. y Starobin, S. S. (2015). A comparative study of student engagement, satisfaction, and academic success among international and american students. Journal of International Students, 5(1), 72-85. http://jistudents.org

Le, T., Bolt, D., Camburn, E., Goff, P. y Rohe, K. (2017). Latent Factors in Student-Teacher Interaction Factor Analysis. Journal of Educational and Behavioral Statistics, 42(2), 115-144. https://doi.org/10.3102/1076998616676407

Leal Filho, W., Shiel, C. y Paço, A. (2016). Implementing and operationalising integrative approaches to sustainability in higher education: the role of project-oriented learning. Journal of Cleaner Production, 133, 126-135. https://doi.org/10.1016/j.jclepro.2016.05.079

Livengood, J. M. (1992). Students’ motivational goals and beliefs about effort and ability as they relate to college academic success. Research in Higher Education, 33(2), 247-261. https://doi.org/10.1007/BF00973581

Lizzio, A., Wilson, K. y Simons, R. (2002). University students’ perceptions of the learning environment and academic outcomes: Implications for theory and practice. Studies in Higher Education, 27(1), 27-52. https://doi.org/10.1080/03075070120099359

Marginson, S. (2014). Higher education and public good. In Thinking About Higher Education (Vol. 9783319032, Issue 4, pp. 53-69). Wiley/Blackwell (10.1111). https://doi.org/10.1007/978-3-319-03254-2-5

Mishra, B. K. y Sahoo, A. K. (2016). Evaluation of faculty performance in education system using classification technique in opinion mining based on GPU, Advances in Intelligent Systems and Computing, 411, 109-119. https://doi.org/10.1007/978-81-322-2731-1_10

Mishra, S. (2020). Social networks, social capital, social support and academic success in higher education: A systematic review with a special focus on ‘underrepresented’ students. Educational Research Review, 29, 100307. https://doi.org/10.1016/j.edurev.2019.100307

Nagda, B. A., Gregerman, S. R., Jonides, J., Von Hippel, W. y Lerner, J. S. (1998). Undergraduate student-faculty research partnerships affect student retention. In Review of Higher Education, 22(1), 55-72. https://doi.org/10.1353/rhe.1998.0016

Nasser-Abu Alhija, F. (2017). Teaching in higher education: Good teaching through students’ lens. Studies in Educational Evaluation, 54, 4-12. https://doi.org/10.1016/j.stueduc.2016.10.006

Pascarella, E. T., Edison, M., Hagedorn, L. S., Nora, A. y Terenzini, P. T. (1996). Influences on students’ internal locus of attribution for academic success in the first year of college. Research in Higher Education, 37(6), 731-756. https://doi.org/10.1007/BF01792954

Pineda, C., Bermúdez, J.-J., Rubiano, Á., Pava, N., Suárez, R. y Cruz, F. (2014). Student engagement and academic performance in the colombian university context. RELIEVE - Revista Electronica de Investigacion y Evaluacion Educativa, 20(2), 1-19. https://doi.org/10.7203/relieve.20.2.4238

R CoreTeam, D. C. (2019). A Language and Environment for Statistical Computing. In R Foundation for Statistical Computing (Vol. 739, Issue 09/18/2009, p. ISBN 3-900051-07-0-ISBN 3-900051-07-0). https://doi.org/10.1007/978-3-540-74686-7

Respondek, L., Seufert, T., Stupnisky, R. y Nett, U. E. (2017). Perceived academic control and academic emotions predict undergraduate university student success: Examining effects on dropout intention and achievement. Frontiers in Psychology, 8(MAR), 243. https://doi.org/10.3389/fpsyg.2017.00243

Roksa, J. y Whitley, S. E. (2017). Fostering Academic Success of First-Year Students: Exploring the Roles of Motivation, Race, and Faculty. Journal of College Student Development, 58(3), 333-348. https://doi.org/10.1353/csd.2017.0026

Romanski, P. y Kotthoff, L. (2016). FSelector: Selecting Attributes. https://cran.r-project.org/package=FSelector

Salminen-Tuomaala, M. y Koskela, T. (2020). How can simulation help with learning project work skills? Experiences from higher education in Finland. Educational Research, 62(1), 77-94. https://doi.org/10.1080/00131881.2020.1711791

Sanvitha, K. T., Liyanage, S. R. y Bhatt, C. M. (2018). A data mining approach to identify the factors affecting the academic success of tertiary students in sri lanka. Lecture Notes on Data Engineering and Communications Technologies, 11, 179-197. https://doi.org/10.1007/978-3-319-68318-8_9

Shetu, S. F., Saifuzzaman, M., Moon, N. N., Sultana, S. y Yousuf, R. (2021). Student’s performance prediction using data mining technique depending on overall academic status and environmental attributes. Advances in Intelligent Systems and Computing, 1166, 757-769. https://doi.org/10.1007/978-981-15-5148-2_66

Souchon, N., Kermarec, G., Trouilloud, D. y Bardin, B. (2020). Influence of teachers’ political orientation and values on their success prediction toward students from different socioeconomic background. Revue Europeenne de Psychologie Appliquee, 70(5), 100553. https://doi.org/10.1016/j.erap.2020.100553

Struyven, K., Dochy, F. y Janssens, S. (2003). Students’ Perceptions about New Modes of Assessment in Higher Education: A Review BT - Optimising new modes of assessment: In search of qualities and standards. Optimising New Modes of Assessment: In Search of Qualities and Standards, 1(Chapter 8), 171-223. https://doi.org/10.1007/0-306-48125-1_8

Tinto, V. (1975). Dropout from Higher Education: A Theoretical Synthesis of Recent Research. Review of Educational Research, 45(1), 89-125. https://doi.org/10.3102/00346543045001089

Trigwell, K., Prosser, M. y Waterhouse, F. (1999). Relations between teachers’ approaches to teaching and students’ approaches to learning. Higher Education, 37(1), 57-70. https://doi.org/10.1023/A:1003548313194

Trolian, T. L., Jach, E. A. y Archibald, G. C. (2021). Shaping Students’ Career Attitudes toward Professional Success: Examining the Role of Student-Faculty Interactions. Innovative Higher Education, 46(2), 111-131. https://doi.org/10.1007/s10755-020-09529-3

Valadas, S. T., Almeida, L. S. y Araújo, A. M. (2017). The Mediating Effects of Approaches to Learning on the Academic Success of First-Year College Students. Scandinavian Journal of Educational Research, 61(6), 721-734. https://doi.org/10.1080/00313831.2016.1188146

Van den Berg, M. N. y Hofman, W. H. A. (2005). Student success in university education: A multi-measurement study of the impact of student and faculty factors on study progress. Higher Education, 50(3), 413-446. https://doi.org/10.1007/s10734-004-6361-1

Van Herpen, S. G. A., Meeuwisse, M., Hofman, W. H. A., Severiens, S. E. y Arends, L. R. (2017). Early predictors of first-year academic success at university: pre-university effort, pre-university self-efficacy, and pre-university reasons for attending university. Educational Research and Evaluation, 23(1-2), 52-72. https://doi.org/10.1080/13803611.2017.1301261

Vo, T. N. C., Nguyen, H. P. y Vo, T. N. T. (2016). Making kernel-based vector quantization robust and effective for incomplete educational data clustering. Vietnam Journal of Computer Science, 3(2), 93. https://doi.org/10.1007/s40595-016-0060-6

Walder, A. M. (2017). Pedagogical Innovation in Canadian higher education: Professors’ perspectives on its effects on teaching and learning. Studies in Educational Evaluation, 54, 71-82. https://doi.org/10.1016/j.stueduc.2016.11.001

Winterer, E. R., Froyd, J. E., Borrego, M., Martin, J. P. y Foster, M. (2020). Factors influencing the academic success of Latinx students matriculating at 2-year and transferring to 4-year US institutions—implications for STEM majors: a systematic review of the literature. In International Journal of STEM Education 7(1), 34. https://doi.org/10.1186/s40594-020-00215-6

Young, P., Glogowska, M. y Lockyer, L. (2007). Conceptions of early leaving: A comparison of the views of teaching staff and students. Active Learning in Higher Education, 8(3), 275-287. https://doi.org/10.1177/1469787407081882

How to Cite

Guanin-Fajardo, J. H., & Casillas Barranquero, J. (2022). University context, teachers and students: links and academic success. Iberoamerican Journal of Education, 88(1), 127–146. https://doi.org/10.35362/rie8814733

Published

2022-03-01

Issue

Section

Educación superior en Iberoamérica: impactos de los sistemas de aseguramiento de