The Influence on Academic Performance of Working Group Methodology

Icíar Carmen Jiménez Barandalla; José Luis Montes Botella; Paloma Bernal Turnes

doi:doi:10.11648/j.her.20180302.11

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The Influence on Academic Performance of Working Group Methodology

Icíar Carmen Jiménez Barandalla, José Luis Montes Botella, Paloma Bernal Turnes

Published in Higher Education Research (Volume 3, Issue 2)

Received: 13 February 2018 Accepted: 8 May 2018 Published: 24 May 2018

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Abstract

The Working Group Methodology has positive effects on students’ academic performance. The contribution of this study consists in determining the variables by means of which the Working Group Methodology influences academic performance, and in comparing the effectiveness of two different working group methodologies: cooperative learning (hereafter CL) and group work without guidelines established by the teacher, known as the Unstructured Groups Methodology (hereafter UGM). To that end, the effect of Working Group Methodology on academic performance is measured using three factors: 1) student attitudes; 2) attitude to learning and the learning approach adopted by students; and 3) student skills. The sample is made up of 110 students from a Spanish university, working on the Corporate Finance module of a degree in Business Administration and Management. Based on the analysis of Structural Equation Modeling the conclusion is reached that only the CL methodology affects academic performance, and that it does so via student skills; its influence via the attitude to learning and the learning approach of the student is also debated. In addition, it can be seen that CL influences student attitudes and skills in a more significant way than UGM. Finally, the results show that the variables in the model account for academic performance to a greater extent in the group in which CL was used (R²=0.264) than in the group in which UGM was applied (R²=0.187). These results demonstrate the greater effectiveness of group work when based on well-defined guidelines, rather than when developed without a predefined structure.

Published in	Higher Education Research (Volume 3, Issue 2)
DOI	10.11648/j.her.20180302.11
Page(s)	23-31
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Academic Performance, Working Group, Cooperative Learning, Skills, Attitudes, Learning Approach

References

[1]	Mittelmeier, J., Rienties, B., Tempelaar, D., and Whitelock, D. (2018). Overcoming cross-cultural group work tensions: Mixed student perspectives on the role of social relationships. Higher Education, 75(1), 149-166. doi:10.1007/s10734-017-0131-3
[2]	Lavy, S. (2017). Who benefits from group work in higher education? An attachment theory perspective. Higher Education, 73(2), 175-187. doi:10.1007/s10734-016-0006-z
[3]	Webb, N. M. (1982). Student interaction and learning in small groups. Review of Educational Research, 52(3), 421-445. doi:10.3102/00346543052003421
[4]	Johnson, D. W., and Johnson, R. T. (1999). What makes cooperative learning work. In D. Kluge, S. McGuire, D. W. Johnson, and R. T. Johnson (Eds.), Cooperative learning (pp. 23-36). Tokio: Japan Association for Language Teaching.
[5]	Stahl, G. (2012) Traversing planes of learning. International Journal of Computer-Supported Collaborative Learning, 7, 467-473. doi:10.1007/s11412-012-9159-7
[6]	Johnson, D. W., Johnson, R. T., and Holubec, E. J. (1999). Los nuevos círculos del aprendizaje. La cooperación en el aula y la escuela [The new circles of learning. Cooperation in the classroom and school]. Buenos Aires: Aiqué.
[7]	Brown, A. (1994) Group Work. Great Yarmouth: Ashgate Publishing.
[8]	Handy, C. B. (1983). Understanding organizations. Middlesex, UK: Penguin Books Ltd.
[9]	Crow, L. D. and Crow, A. (1969). Adolescent development and adjustment. New York: Mc Graw-Hill.
[10]	Minbashian, A., Huon, G. F., and Bird, K. D. (2004). Approaches to studying and academic performance in short-essay exams. Higher Education, 47(2), 161-176. doi:10.1023/B:HIGH.0000016443.43594.d1
[11]	Dockery, T. M., and Bedeian, A. G. (1988). “Attitudes versus actions”: LaPiere's (1934) Classic study revisited. Social Behavior and Personality, 17(1), 9-16. doi:10.2224/sbp.1989.17.1.9
[12]	Pérez, M. V., Valenzuela, M., Díaz, A., González-Pienda, J. A., and Núñez, J. C. (2013). Dificultades de aprendizaje en estudiantes universitarios de primer año [Learning difficulties in college freshmen]. Atenea, 508, 135-150. doi:10.4067/S0718-04622013000200010
[13]	Brown, P., Green, A., and Lauder, H. (2001). High Skills. Globalization, Competitiveness, and Skill Formation. Oxford, UK: Oxford University Press.
[14]	Woods, D. R., Felder, R. M., Rugarcia, A., and Stice, J. E. (2000). The future of Engineering education III. Developing critical skills. Chemical Engineering Education, 34(2), 108-117. Retrieved from: http://www.che.ufl.edu/cee/
[15]	Lovelace, M., and Brickman, P. (2013). Best practices for measuring students’ attitudes toward learning science. CBE-Life Sciences Education 12(4), 606-617. doi:10.1187/cbe.12-11-019
[16]	Shaoan, X. I. E. (2013). Research on students’ study condition and psychology for interactive teaching model in the university. Psychology Research, 13, 1838 - 658X. doi:10.5503/J.PR.2013.13.002
[17]	Gardner, R. C., and MacIntyre, P. D. (1993). On the measurement of affective variables in second language learning. Language learning, 43(2), 157-194. doi:10.1111/j.1467-1770.1992.tb00714.x
[18]	Heikkilä, A., Niemivirta, M., Nieminen, J., and Lonka, K. (2011). Interrelations among university students' approaches to learning, regulation of learning, and cognitive and attributional strategies: A person oriented approach. Higher Education, 61(5), 513-529. doi:10.1007/s10734-010-9346-2
[19]	Booth, K. M., and James, B. W. (2001). Interactive learning in a higher education Level 1 mechanics module. International Journal of Science Education, 23(9), 955-967. doi:10.1080/09500690119817
[20]	Tran, D. V., and Lewis. R. R. (2012). Effects of cooperative learning on students at a Giang university in Vietnam. International Education Studies, 5(1), 86-99. doi:10.5539/ies.v5n1p86
[21]	Bailey, J., Sass, M., Swiercz, P. M., Seal, C., and Kayes, D. C. (2005). Teaching with and through teams: Student-written, instructor-facilitated case writing and the signatory code. Journal of Management Education, 29(1), 39-59. doi:10.1177/1052562904269641
[22]	López, C., and Real, J. C. (2017). Efectos de la aplicación de "jigsaw" sobre la adquisición de competencias en dirección de operaciones. Revista De Métodos Cuantitativos Para La Economía y La Empresa, 24, 220-249. Retrieved from https://vpnssl.urjc.es/dana/home/index.cgi/docview/2013608402?accountid=14730
[23]	Jordan, D., and Le Metaias, J. (1997). Social skilling through cooperative learning. Educational Research, 39(1), 3-21. doi:10.1080/0013188970390101
[24]	Whicker, K. M., Bol, L., and Nunerery, J. A. (1997). Cooperative learning in the Secondary Mathematics Classroom. The Journal of Educational Research, 91(1), 42-48. doi:10.1080/00220679709597519
[25]	Springer, L., Stanne, M. E., & Donovan, S. S. (1999). Effects of small-group learning on undergraduates in science, mathematics, engineering, and technology: A meta-analysis. Review of Educational Research, 69(1), 21-51. doi:10.3102/00346543069001021
[26]	Hänze, M. and Berger, R. (2007). Cooperative learning, motivational effects, and student characteristics: An experimental study comparing cooperative learning and direct instruction in 12th grade physics classes. Learning and Instruction, 17, 29-4. doi:10.1016/j.learninstruc.2006.11.004
[27]	Bertucci, A., Conte, S., Johnson, D. W., and Johnson, R. T. (2010). The impact of size of cooperative group on achievement, social support, and self-esteem. The Journal of General Psychology, 137(3), 256-272. doi:10.1080/00221309.2010.484448
[28]	Mamat, N. J. Z., and Mazelan, F. F. (2011). Learning encouragement factors and academic performance. Procedia - Social and Behavioral Sciences, 18, 307-315. doi:10.1016/j.sbspro.2011.05.044
[29]	Kesici, S., Sahin, I., and Akturk, H. O. (2009). Analysis of cognitive learning strategies and computer attitudes, according to college students’ gender and locus of control. Computers in Human Behavior, 25, 529-534. doi:10.1016/j.chb.2008.11.004
[30]	Credé, M., and Kuncel, N. R. (2008). Study habits, skills, and attitudes: The third pillar supporting collegiate academic performance. Perspectives on Psychological Science, 3(6), 425-454. doi:10.1111/j.1745-6924.2008.00089.x
[31]	Trigwell, K. and Prosser, M. (1991). Relating approaches to study and quality of learning outcomes at the course level. British Journal of Educational Psychology 61(3), 265-275. doi:10.1111/j.2044-8279.1991.tb00984.x
[32]	Teachman, J. D. (1996). Intellectual Skill and Academic Performance: Do Families Bias the Relationship? Sociology of Education, 69(1), 35-48. doi:10.2307/2112722
[33]	Ringle, C. M., Wende, S., and Will, A. (2005). SmartPLS 2.0.M3. Hamburg. Retrieved from: www.smartpls.de
[34]	Henseler, J., Ringle, C. M., and Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing 20, 277-320. doi:10.1108/s1474-7979(2009)0000020014
[35]	Entwistle, N. J., and Ramsden, P. (1983). Understanding student learning. London: Croom Helm.
[36]	Biggs, J. B. (2001). Enhancing learning: A matter of style or approach? In R. J. Sternberg, and L. Zhang (Eds.), Perspectives on thinking, learning, and cognitive styles (pp. 73-102). Mahwah, NJ: Lawrence Erlbaum Associates.
[37]	Geffen, D., Straub, D. W., and Boudreau, M. (2000). Structural Equations Models and Regression: Guidelines for Research Practice. In Communications of the Association for Information Systems, Vol. 4, Article 7 (pp. 1-79). doi:10.2307/3250956
[38]	Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. doi:10.2307/3151312
[39]	Werts, C. E., Linn, R. L., and Jöreskog, K. G. (1974). Interclass reliability estimates: Testing structural assumption. Educational and Psychological Measurement, 34(1), 25-33. doi:10.1177/001316447403400104
[40]	Vallet-Bellmunt, T., Rivera-Torres, P., Vallet-Bellmunt, I., and Vallet-Bellmunt, A. (2017). Aprendizaje cooperativo, aprendizaje percibido y rendimiento académico en la enseñanza del marketing. Educación XX1, 20(1). doi:10.5944/educxx1.17512
[41]	Lobato, C., Apodaca, P. M., Barandiarán, M. C., San José, M. J., Sancho, J. and Zubimendi, J. L. (2010). Development of the competences of teamwork through cooperative learning at the university. International Journal of Information and Operations Management Education, 3(3), 224-240. doi: 10.1504/IJIOME.2010.033547
[42]	Slavin, R. E. (1996). Research on cooperative learning and achievement: What we know, what we need to know. Contemporary Educational Psychology, 21(1), 43-69. doi:10.1006/ceps.1996.0004
[43]	Webb, L. D., and Brigman, G. A. (2006). Student success skills: Tools and strategies for improved academic and social outcomes. Professional School Counseling, 10(2), 112-120. Retrieved from: http://eric.ed.gov/?id=EJ767362

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Icíar Carmen Jiménez Barandalla, José Luis Montes Botella, Paloma Bernal Turnes. (2018). The Influence on Academic Performance of Working Group Methodology. Higher Education Research, 3(2), 23-31. https://doi.org/10.11648/j.her.20180302.11

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Icíar Carmen Jiménez Barandalla; José Luis Montes Botella; Paloma Bernal Turnes. The Influence on Academic Performance of Working Group Methodology. High. Educ. Res. 2018, 3(2), 23-31. doi: 10.11648/j.her.20180302.11

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AMA Style

Icíar Carmen Jiménez Barandalla, José Luis Montes Botella, Paloma Bernal Turnes. The Influence on Academic Performance of Working Group Methodology. High Educ Res. 2018;3(2):23-31. doi: 10.11648/j.her.20180302.11

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@article{10.11648/j.her.20180302.11,
  author = {Icíar Carmen Jiménez Barandalla and José Luis Montes Botella and Paloma Bernal Turnes},
  title = {The Influence on Academic Performance of Working Group Methodology},
  journal = {Higher Education Research},
  volume = {3},
  number = {2},
  pages = {23-31},
  doi = {10.11648/j.her.20180302.11},
  url = {https://doi.org/10.11648/j.her.20180302.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.her.20180302.11},
  abstract = {The Working Group Methodology has positive effects on students’ academic performance. The contribution of this study consists in determining the variables by means of which the Working Group Methodology influences academic performance, and in comparing the effectiveness of two different working group methodologies: cooperative learning (hereafter CL) and group work without guidelines established by the teacher, known as the Unstructured Groups Methodology (hereafter UGM). To that end, the effect of Working Group Methodology on academic performance is measured using three factors: 1) student attitudes; 2) attitude to learning and the learning approach adopted by students; and 3) student skills. The sample is made up of 110 students from a Spanish university, working on the Corporate Finance module of a degree in Business Administration and Management. Based on the analysis of Structural Equation Modeling the conclusion is reached that only the CL methodology affects academic performance, and that it does so via student skills; its influence via the attitude to learning and the learning approach of the student is also debated. In addition, it can be seen that CL influences student attitudes and skills in a more significant way than UGM. Finally, the results show that the variables in the model account for academic performance to a greater extent in the group in which CL was used (R2=0.264) than in the group in which UGM was applied (R2=0.187). These results demonstrate the greater effectiveness of group work when based on well-defined guidelines, rather than when developed without a predefined structure.},
 year = {2018}
}

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TY  - JOUR
T1  - The Influence on Academic Performance of Working Group Methodology
AU  - Icíar Carmen Jiménez Barandalla
AU  - José Luis Montes Botella
AU  - Paloma Bernal Turnes
Y1  - 2018/05/24
PY  - 2018
N1  - https://doi.org/10.11648/j.her.20180302.11
DO  - 10.11648/j.her.20180302.11
T2  - Higher Education Research
JF  - Higher Education Research
JO  - Higher Education Research
SP  - 23
EP  - 31
PB  - Science Publishing Group
SN  - 2578-935X
UR  - https://doi.org/10.11648/j.her.20180302.11
AB  - The Working Group Methodology has positive effects on students’ academic performance. The contribution of this study consists in determining the variables by means of which the Working Group Methodology influences academic performance, and in comparing the effectiveness of two different working group methodologies: cooperative learning (hereafter CL) and group work without guidelines established by the teacher, known as the Unstructured Groups Methodology (hereafter UGM). To that end, the effect of Working Group Methodology on academic performance is measured using three factors: 1) student attitudes; 2) attitude to learning and the learning approach adopted by students; and 3) student skills. The sample is made up of 110 students from a Spanish university, working on the Corporate Finance module of a degree in Business Administration and Management. Based on the analysis of Structural Equation Modeling the conclusion is reached that only the CL methodology affects academic performance, and that it does so via student skills; its influence via the attitude to learning and the learning approach of the student is also debated. In addition, it can be seen that CL influences student attitudes and skills in a more significant way than UGM. Finally, the results show that the variables in the model account for academic performance to a greater extent in the group in which CL was used (R2=0.264) than in the group in which UGM was applied (R2=0.187). These results demonstrate the greater effectiveness of group work when based on well-defined guidelines, rather than when developed without a predefined structure.
VL  - 3
IS  - 2
ER  -

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Author Information

Icíar Carmen Jiménez Barandalla

Department of Business Economy, Rey Juan Carlos University, Madrid, Spain
José Luis Montes Botella

Department of Applied Economics, Rey Juan Carlos University, Madrid, Spain
Paloma Bernal Turnes

Department of Business Economy, Rey Juan Carlos University, Madrid, Spain

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APA Style

Icíar Carmen Jiménez Barandalla, José Luis Montes Botella, Paloma Bernal Turnes. (2018). The Influence on Academic Performance of Working Group Methodology. Higher Education Research, 3(2), 23-31. https://doi.org/10.11648/j.her.20180302.11

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ACS Style

Icíar Carmen Jiménez Barandalla; José Luis Montes Botella; Paloma Bernal Turnes. The Influence on Academic Performance of Working Group Methodology. High. Educ. Res. 2018, 3(2), 23-31. doi: 10.11648/j.her.20180302.11

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AMA Style

Icíar Carmen Jiménez Barandalla, José Luis Montes Botella, Paloma Bernal Turnes. The Influence on Academic Performance of Working Group Methodology. High Educ Res. 2018;3(2):23-31. doi: 10.11648/j.her.20180302.11

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@article{10.11648/j.her.20180302.11,
  author = {Icíar Carmen Jiménez Barandalla and José Luis Montes Botella and Paloma Bernal Turnes},
  title = {The Influence on Academic Performance of Working Group Methodology},
  journal = {Higher Education Research},
  volume = {3},
  number = {2},
  pages = {23-31},
  doi = {10.11648/j.her.20180302.11},
  url = {https://doi.org/10.11648/j.her.20180302.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.her.20180302.11},
  abstract = {The Working Group Methodology has positive effects on students’ academic performance. The contribution of this study consists in determining the variables by means of which the Working Group Methodology influences academic performance, and in comparing the effectiveness of two different working group methodologies: cooperative learning (hereafter CL) and group work without guidelines established by the teacher, known as the Unstructured Groups Methodology (hereafter UGM). To that end, the effect of Working Group Methodology on academic performance is measured using three factors: 1) student attitudes; 2) attitude to learning and the learning approach adopted by students; and 3) student skills. The sample is made up of 110 students from a Spanish university, working on the Corporate Finance module of a degree in Business Administration and Management. Based on the analysis of Structural Equation Modeling the conclusion is reached that only the CL methodology affects academic performance, and that it does so via student skills; its influence via the attitude to learning and the learning approach of the student is also debated. In addition, it can be seen that CL influences student attitudes and skills in a more significant way than UGM. Finally, the results show that the variables in the model account for academic performance to a greater extent in the group in which CL was used (R2=0.264) than in the group in which UGM was applied (R2=0.187). These results demonstrate the greater effectiveness of group work when based on well-defined guidelines, rather than when developed without a predefined structure.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - The Influence on Academic Performance of Working Group Methodology
AU  - Icíar Carmen Jiménez Barandalla
AU  - José Luis Montes Botella
AU  - Paloma Bernal Turnes
Y1  - 2018/05/24
PY  - 2018
N1  - https://doi.org/10.11648/j.her.20180302.11
DO  - 10.11648/j.her.20180302.11
T2  - Higher Education Research
JF  - Higher Education Research
JO  - Higher Education Research
SP  - 23
EP  - 31
PB  - Science Publishing Group
SN  - 2578-935X
UR  - https://doi.org/10.11648/j.her.20180302.11
AB  - The Working Group Methodology has positive effects on students’ academic performance. The contribution of this study consists in determining the variables by means of which the Working Group Methodology influences academic performance, and in comparing the effectiveness of two different working group methodologies: cooperative learning (hereafter CL) and group work without guidelines established by the teacher, known as the Unstructured Groups Methodology (hereafter UGM). To that end, the effect of Working Group Methodology on academic performance is measured using three factors: 1) student attitudes; 2) attitude to learning and the learning approach adopted by students; and 3) student skills. The sample is made up of 110 students from a Spanish university, working on the Corporate Finance module of a degree in Business Administration and Management. Based on the analysis of Structural Equation Modeling the conclusion is reached that only the CL methodology affects academic performance, and that it does so via student skills; its influence via the attitude to learning and the learning approach of the student is also debated. In addition, it can be seen that CL influences student attitudes and skills in a more significant way than UGM. Finally, the results show that the variables in the model account for academic performance to a greater extent in the group in which CL was used (R2=0.264) than in the group in which UGM was applied (R2=0.187). These results demonstrate the greater effectiveness of group work when based on well-defined guidelines, rather than when developed without a predefined structure.
VL  - 3
IS  - 2
ER  -

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