Attitudes to Learning, Learning Strategies and Learning Approaches in University Students

Session Information

22 SES 05.5 PS, General Poster Session

General Poster Session

Time:
2014-09-03
12:30-14:00
Room:
Poster Area C (between B019 - B024)
Chair:

Contribution

Do university students with better attitudes toward learning have better learning strategies compared to those students with poor attitudes? Do they also prefer deep learning approaches? These are the research questions that guide our work. We believe that this relationship does exist and that students with better attitudes will have better learning strategies and will prefer deep learning approaches. The objective of this work is to check whether such relationships exist within university students in the selected sample.

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

We start from a conception of the attitude as a tendency or learned predisposition, relatively durable, to evaluate in a certain way an object, person, group, event or situation, based on the available beliefs around the same. This tendency or predisposition leads to act favorably or unfavorably towards that object, person, group, event or situation, in a consistent manner with that evaluation. Therefore, attitudes are stable predispositions to value and act based on a relatively enduring organization of beliefs about reality that predisposes people to act in a certain way (Escámez, Garcia, Perez & Llopis, 2007; Escámez & Ortega, 1986; Garcia & Sales, 1997; Rokeach, 1979; Wander Zanden, 1989).

The relationship between attitudes and academic performance has been studied principally in primary and secondary students. In fact, there are works that reflect the relationship between attitudes and performance in such students. Akey (2006), Quiles (1993) and Ramirez (2005) works are some examples of what we say. There are also some studies that analyze the influence of attitudes on the performance of university students (Gargallo, Pérez, Serra, Sanchez & Ros, 200; Goolsby, 1988; House & Prion, 1998). However we don’t have found works that explain the keys of that relationship. In this sense, our work is trying to explain these keys, analyzing whether students with better attitudes also manage better learning strategies and use deep learning approaches. If this is checked, the relationship between attitudes, learning and performance may possibly be explained.

The Bologna process of convergence, in which many European countries are involved recommends a university pedagogy that is based on the model learning centered (student-centered learning, learning paradigm) (Attard, Di Ioio, Geven & Santa, 2010, Biggs, 2005; Kember, 2009; Monereo &  Pozo, 2003; Samuelowicz & Bain, 2001).

This model requires to teachers to undergo new teaching and evaluation methods and also demand greater student engagement, which is a key element of the process. Students must have an especially active role in this process to become more,  autonomous and self-regulated learners (Hannafin, 2012, Machemer & Crawford, 2007).

In our opinion, if attitudes to learning are critical in the process and influence the strategies and approaches to learning of students, as we think, we can offer to other Spanish and European universities relevant data and training proposals of interest. To check it we are collecting data from students of three universities in the city of Valencia (Spain).


[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 consisted of 686 students from different degrees from the three universities of Valencia (Spain): 360 students were from the University of Valencia, 193 were from the Poytechnical University of Valencia, and 103 from the Catholic University of Valencia. The sampling method is purposeful sampling, since participants were selected from a sampling of teachers who apply innovative methods that are learning centered. Participants belong to three branches of knowledge: Education, Health and Engineering. In the first 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 three questionnaires. 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. Learning approaches were assessed by means of the R-SPQ-2 (Biggs, Kember & Leung, 2001). It comprises 20 items, divided into two subscales: one surface approach sub-scale (α=.795) and another deep approach sub-scale (α=.812), each of them consists of 10 items. The attitudes towards learning were assessed by means of the AUSLQ, (Attitudes of University Students toward Learning Questionnaire) (Gargallo, Pérez, Fernández & Jiménez, 2007). It comprises 11 items, organised in three dimensions: 1) Positive attitude towards deep learning; engagement to active learning, etc., 2) Positive attitude towards teamwork, and 3) Internal atributions. It was constructed using Likert-scale format with five possible answers. Items were formulated following Fishbein and Ajzen model (1975, 1980), Ajzen (1990). The reliability for all the questionnaire was α = .683. The information was gathered through on-line questionnaires. Statistical analyses, performed by SPSS 19.0, were descriptive and ANOVA.

Expected Outcomes

The results obtained from students in total score of attitudes were used to classify students into three groups according to their management, using the percentile scores: A "low" group of attitudes, made up of students placed below the 25th percentile, an "average" group, consisting of students located between the 25th and 75th, and a "high" group, consisting of students located above the 75th percentile. Afterwards, it was carried out one-way ANOVA to verify the possible differences between the three groups in learning strategies and in learning approaches. To do so, the scores obtained by students of the three groups in motivational, affective, metacogitive, contextual control, search and processing and use of information strategies were taken. Inclusive were the scores of surface and deep approach. The results of the ANOVA showed significant differences (p <.001) among the three groups in all variables, with a value of partial eta squared ranging from small and medium. Then post-hoc tests (Scheffe) were performed to analyze between which groups significant differences existed. They were found in the six learning strategies scales analyzed, favoring the average group compared to the low group and high group compared to both of them. This implies that the better attitudes the students had the better strategies they managed. Significant differences in deep approach to learning were also found favoring students of average group versus students of low group and favoring the students of high group versus students of the other two groups. This also happened in the surface learning approach. The better attitudes to learning the students had, the more the surface learning approach decreased and the deep approach to learning increased. Therefore, the attitudes appear to be a key element in the process and professors should work in their classes to empower the learning attitudes of the university students.

References

Attard, A., Di Ioio, E., Geven, K. & Santa, R. (2010). Student centered learning. An insight into theory and practice.Bucarest: Partos Timisoara. Akey, T. (2006). School context, student attitudes and behaviour, and academic achievement: An exploratory analysis. Informe de investigación. http://www.eric.ed.gov/ERICDocs/data/ericdocs2/content_storage_ 01/0000000b/80/31/25/01.pdf Ajzen, I. (1990). The theory of planned behavior. Organizational behavior and human decision processes, 50, 179-211. Biggs, J. (2005). Calidad del aprendizaje universitario. Madrid: Narcea. Biggs, J., Kember, D. & Leung, D.Y.P. (2001). The revised two-factor Study Process Questionnaire: R-SPQ-2. British Journal of Educational Psychology, 71, 133-149. Escámez, J., García, R., Pérez, C. & Llopis, A. (2007). El aprendizaje de actitudes y valores. Teoría y práctica. Barcelona: Octaedro-OEI. Gargallo, B., Pérez, C., Fernández, A. & Jiménez, M.A. (2007). La evaluación de las actitudes ante el aprendizaje de los estudiantes universitarios. El Cuestionario CEVAPU. Teoría de la Educación. Educación y Cultura en la Sociedad de la Información, 8 (2), 238-258. Gargallo, B., Pérez, C., Serra, B., Sánchez, F. & Ros, I. (2007). Actitudes ante el aprendizaje y rendimiento académico en estudiantes universitarios. Revista Iberoamericana de Educación, 42 (1), 1-11. 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. En N.M. Seel (Ed.), Encyclopedia of the Sciences of Learning (pp. 3211-3214). Nueva York: Springer. House, J.D. & Prion, S.K. (1998). Student attitudes and academic background as predictors of achievement in college English. International Journal of Instructional Media, 25 (1), 29-42. Kember, D. (2009). Promoting student-centred forms of learning across an entire university. Higher Education, 58, 1-13. 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. Quiles, Mª.N. (1993). Actitudes hacia las matemáticas y rendimiento escolar. CL&E. Comunicación, Lenguaje y Educación, 18, 115-125. Ramírez, Mª.J. (2005). Actitudes hacia las matemáticas y rendimiento académico entre estudiantes de octavo básico. Estudios pedagógicos, 31 (1), 97-112. Rokeach, M. (1970). Beliefs, Acttitudes and values.San Francisco. Jossey-Bass. Samuelowicz, K. & Bain, J.D. (2001). Revisiting academics’ beliefs about teaching and learning, Higher Education, 41, 299-325. Vander Zanden, J.W.(1989). Manual de psicología social. Buenos Aires, Paidós.

Author Information

Bernardo Gargallo López (presenting / submitting)
University of Valencia, Spain
University of Valencia, Spain
Universidad de Valencia
Teoría de la Educación
Valencia
University of Valencia, Spain
Polytechnic University of Valencia, Spain
Catholic University of Valencia, Spain

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