Active Learning, Teaching for Understanding, and Learning Approaches in University Students

Session Information

27 SES 07 A, Teaching Practices in Higher Education

Paper/Poster Session

Time:
2015-09-09
17:15-18:45
Room:
201.Oktatóterem [C]
Chair:
Alain Jameau
Discussant:
Meinert Arnd Meyer

Contribution

Do the learning methods focused on active learning and on teaching for understanding improve the learning strategies of university students? This is the research question that guides our work.

The results here enclosed are derived from a three-year research whose goals are obviously larger[1].

            We understand the active learning and the teaching for understanding as Kember and Leung (2009) do, who interpret the first one as the ability to use a variety of teaching methods and to give the students the opportunity of participating in lectures, and the second one as the ability to help the students to understand the contents of the course, as it is assessed in the SEQ questionnaire (Student Engagement Questionnaire) (Kember & Leung, 2009).

Underlying learning theories in the Bologna process of convergence, defend a university pedagogy focused on learning/learner-centered (student-centered learning, learning paradigm) (Attard, Di Iorio, Geven & Santa, 2010, Biggs, 2005; Kember, 2009; Monereo and Pozo, 2003; Samuelowicz & Bain, 2001).

This model provides professors new teaching and evaluation methods but also demand greater student engagement, which is a key element of the process, and who has to hold an especially active role in it, becoming an autonomous and self-regulated learner (Hannafin, 2012, Machemer & Crawford, 2007).

            This is a model that demands self-regulated learners (Attard et al., 2010).

A self-regulated learner (Pintrich, 2000, Zimmerman, 2002) effectively manages the learning strategies, including cognitive and affective-motivational components of support ("to want"), metacognitive components ("to make decisions and to evaluate") and cognitive components ("to be able to”). These are the three components of the model of Weinstein, Husman and Dierking (2000) -"will", "self-regulation" and "skill"- on which researchers basically agree (Yip, 2012). 

In this context, it is relevant to verify whether, as we suppose, the professors who promote the active learning and who teach for the understanding help the students to improve their learning strategies (motivational, affective, metacognitive, contextual control strategies, information search strategies and information processing strategies). This is the objective that we address in this work.

To pursue this objective we are collecting data from students of three universities in the city of Valencia (Spain).

In our research, we work with professors who use learner-centered methods, which, we think, can help develop active learning and the teaching for understanding and, as a consequence, it can improve the learning strategies in university students

If the results confirm our assumptions, we can offer to other Spanish and European universities relevant data and training proposals of interest.

In addition, there is convincing evidence that learning strategies influence student achievement (Pintrich, 1995; Gargallo, Suárez-Rodríguez & Pérez-Pérez, 2009), and also learning approaches: (Gargallo, 2008; Valle, Gonzalez Cabanach Núñez, Suárez Piñeiro & Rodríguez, 2000), so the interest of this work is clear.

[1] It is the "Learning-centered methodologies at the university. Design, implementation and assessment”, approved by the Spanish Economy and Competitiveness’ Ministry into the National Basic Research Program, 2001 (2013-2015) (Financing Plan E, PGE), directed by Professor Ph.D. Bernardo Gargallo (code EDU2012-32725).

 

Method

The research work is based on a survey design. The sample included 800 students from different degrees and masters programs from three universities in the city of Valencia (Spain): 558 students were from the University of Valencia, 125 were from the Poytechnical University of Valencia, and 117 from the Catholic University of Valencia. The sampling method is purposeful sampling, since participants were selected from a sampling of teachers who apply innovative learning centered methods. Participants belong to three branches of knowledge: Education, Health and Engineering. In the second year of research different data were collected from their students to make a diagnosis of their learning process and in order to make comparisons and to analyze relationships between constructs. The information was collected from two questionnaires. In order to evaluate the engagement of the student we used the SEQ questionnaire (Student Engagement Questionnaire) (Kember & Leung, 2009). It consists of 35 items organized into two scales. The first one evaluates the development of 8 capabilities/factors: critical thinking, creative thinking, self-managed learning, adaptability, problem solving, communication skills, interpersonal skills and group work, use of new technologies. The second one evaluates the development of 9 capabilities/factors that their professors promote or use: active learning, teaching for understanding, feedback to help learning, evaluation, relationship between teachers and students, workload, cooperative learning, and coherence of the curriculum. The questionnaire is constructed using Likert-scale format. Cronbach's alpha coefficient for the factors/capabilities of both scales ranges from 64 to 82. For the purposes of this paper, we will only use data from two capabilities of the second scale, active learning and teaching for understanding. In order to evaluate the learning strategies we used the LSUSQ (Gargallo, Suárez-Rodríguez & Pérez-Pérez, 2009). This 88-item questionnaire is constructed using Likert-scale format with five possible answers for each item. The questionnaire is divided into two scales and six subscales. The first scale, of affective, support and control strategies (α=.776) consists of four subscales: motivational strategies (α=.692), affective components (α=.678), meta-cognitive strategies (α=.766) and context control strategies, social interaction and use of resources strategies (α=.768). The second scale, of strategies related to information processing (α=.859) consists of two subscales: Search and selection of information strategies (α=.660) and Processing and use of information strategies (α=.841). The reliability for all the questionnaire is α= .897. The information was gathered through on-line questionnaires. Statistical analyses, performed by SPSS 19.0, were descriptive, MANOVA and ANOVA.

Expected Outcomes

We took the results from the students in critical and creative thinking to classify them using cluster analysis. We found three groups, the first one with low scores in both dimensions, the second one with average scores, and the third one with high scores. Next, a MANOVA analysis was carried out in order to verify the possible differences between the three groups in the six sub-scales of learning strategies. The results showed statistically significant differences in learning strategies (p<.001), with a small effect size (partial eta-squared=.054). Later, a one-way ANOVA test was carried out to verify the possible significant differences existing between the three groups in the learning strategies analyzed: Motivational strategies, Affective components, Meta-cognitive strategies, Context control strategies and social interaction and use of resources strategies, Search and selection of information strategies and Processing and use of information strategies. We found statistically significant differences (p<.001) in all strategies with the only exception of Affective components. In all cases the average scores were higher in the group with high scores in the two dimensions of SEQ, compared to the groups with an average and low score. These scores were also higher in the group with an average score compared to the group with a low score. Then, post-hoc tests (Scheffe) were performed to analyze between which groups significant differences existed. They were found in all strategies, with the only exception of Affective components, favoring the high group compared to the average and the low group. We didn’t found any significant differences between the average and the low group, although the scores were higher in the average group. The results show that those professors, who promote active learning and the teaching for understanding, also improve the learning strategies of university students. Therefore, professors must work to strengthen these methods in class.

References

Attard, A., Di Iorio, E., Geven, K. & Santa, R. (2010). Student centered learning. An insight into theory and practice. Bucarest: Partos Timisoara. Biggs, J. (2005). Calidad del aprendizaje universitario. Madrid: Narcea. Gargallo, B., Suárez-Rodríguez, J. M. & Pérez-Pérez, C. (2009). El cuestionario CEVEAPEU. Un instrumento para la evaluación de las estrategias de aprendizaje de los estudiantes universitarios, RELIEVE, 15: 2, 1-31. Hannafin, M. (2012). Student-Centered Learning. In N.M. Seel (Ed.), Encyclopedia of the Sciences of Learning (pp. 3211-3214). Nueva York: Springer. Kember, D. (2009). Promoting student-centred forms of learning across an entire university. Higher Education, 58, 1-13. Kember, D. & Leung, D.Y.P. (2009): Development of a questionnaire for assessing students’ perceptions of the teaching and learning environment and its use in quality assurance. Learning Environ Res, 12, 15-29. Machemer, P.L. & Crawford, P. (2007). Student perceptions of active learning in a large cross-disciplinary classroom. Active Learning in Higher Education, 8 (1), 9-30. Monereo, C. & Pozo, J.I. (2003). La universidad ante la nueva cultura educativa. Enseñar y aprender para la autonomía. Madrid: Síntesis. Pintrich, P.R. (1995). Understanding self-regulated learning, New Directions for Teaching and Learning, 63, pp. 3-12. Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. Pintrich & M. Zeidner (Eds.), Handbook of Self-Regulation (pp. 451-502). California. Academic Press Samuelowicz, K. & Bain, J.D. (2001). Revisiting academics’ beliefs about teaching and learning, Higher Education, 41, 299-325. Valle, A., González Cabanach, R., Núñez, J., Suárez, J.M., Piñeiro, I. & Rodríguez, S. (2000). Enfoques de aprendizaje en estudiantes universitarios, Psicothema, 12 (3), 368-375. Weinstein, C.E., Husman, J. & Dierking, D. (2002). Self-Regulation Interventions with a focus on learning strategies. In M. Boekaerts, P.R. Pintrich & M. Zeinder, Handbook of Self-regulation (pp. 727-747). San Diego: Academic Press. Yip, M.C.W. (2012). Learning strategies and self-efficacy as predictors of academic performance: a preliminary study. Quality in Higher Education, 18 (1), 23-34. Zimmerman, B.J. (2002). Becoming a self-regulated learner: an overview. Theory into Practice, 41, 64-70.

Author Information

Bernardo Gargallo López (presenting / submitting)
University of Valencia, Spain
Universidad Católica de Valencia
educación
Burjassot (Valencia)
Polytechnic University of Valencia, Spain
Florida Universitaria
Unidad de Educación
Riba-roja del Turia
University of Valencia, Spain
University of Valencia, Spain

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