Personal variables, motivation and avoidance learning strategies in undergraduate students
Introduction
The main objective of this research is to better understand why certain students, even those in the same educational setting, get involved and make an effort to learn using all the resources and strategies they have available, while others make the minimum effort and work to learn. This phenomenon, known by the terms avoidance strategies or work avoidance, reflects passivity or inaction and, when applied to education, refers to those strategies that students should use to learn, but they do not use them. Previous research has suggested that “work avoidance may be an academic goal in which students seek to minimize the amount of work they do at school” (Seifert & O'Keefe, 2001, p. 81).
In order to study this phenomenon, we firstly revised the literature to identify, select, and later evaluate, the most characteristic behaviors that describe students who use avoidance strategies. Secondly, we designed an explicative causal model of such behavior by taking the Educational Situation Quality Model (MCSE ‘Modelo de Calidad de Situación Educativa’), developed by Doménech, 2006, Doménech, 2011a, Doménech, 2011b, Doménech, 2012, Doménech, 2013, as a reference, whose characteristics are briefly commented on below.
The main contribution of this study is to help explain why students use avoidance strategies, which undermine their performance and limit their capacity to learn. As we become capable of understanding why students use avoidance strategies that make their learning difficult by identifying the variables responsible for this behavior, we will be able to design preventive actions in the classroom to improve students' implication and efficacy in their learning. Despite the importance of this issue due to the practical implications derived, studies centered on avoidance strategies are relatively scarce, especially in higher education.
The MCSE could be defined as an instructional model which simultaneously considers the teaching and learning process where motivation plays a central role. It also provides a methodological way to research in the educational setting. As seen in Fig. 1, the model is made up of five blocks of variables arranged into three major sequential phases: input, process and product. The components and variables of the model considered in this study are explained below.
Below, we briefly comment on students' personal variables from Block 1.
According to the constructivist learning approach, prior knowledge facilitates new learning and students' comprehension. Research has verified that individuals with greater prior knowledge of a topic understand and remember more than those with more limited prior knowledge (Schneider & Pressley, 1997). Furthermore, prior knowledge in specific domains has a positive influence on students' learning and achievement (Alexander and Judy, 1988, Dochy et al., 1999, Thompson and Zamboanga, 2004).
The beneficial effects of interest in learning are well-documented (Renninger & Hidi, 2002). The Person–Object Conception of Interest (POI) was developed in the Educational Psychology field. In accordance with this conception, researchers usually adopt the distinction between situational and individual. In the past, many studies have focused on examining the influence of individual interest on learning process and achievement, and the obtained results have verified that level of interest accounts for about 10% of the variance observed in achievement (Schiefele, Krapp, & Winteler, 1992).
The value that a particular task or subject has for students is an important stimulus to generate motivation (Pintrich, 1989, Pintrich and De Groot, 1990). Yet the value that students attribute to a particular subject depends, to a certain extent, on the utility that they perceive it has for them in terms of developing their skills both professionally and personally.
Self-efficacy is a component of Bandura's Social Cognitive Theory (SCT) (1986) and is defined as “an individual's belief in his or her own ability to organize and implement action to produce the desired achievements and results” (Bandura, 1997, p. 3). Perceived self-efficacy that a person has of one's own capabilities to perform or undertake a task increases the likelihood of the task being successfully performed (Bandura, 1986). Prior research has verified that students' self-efficacy beliefs are associated with other motivation constructs and with students' academic performances and achievement (Pajares, 1996, Pajares, 1997).
Self-esteem is the evaluative component of Self-concept, which can be defined as “the positivity of a person's evaluation of self” (Baumeister, 1998, p. 694). Self-esteem has been associated with learning strategies (Núñez et al., 1998), with academic achievement (Mestre, García, Frías, & Llorca, 1992) and with goal progress and intrinsic motivation at school (Vasalampi, Salmela-Aro, & Nurmi, 2010).
The motivational positioning variables (MPV), generated by students at the beginning of the educational process, refer to their initial expectations or ideas about how the teaching/learning process, with a specific subject matter and a specific teacher, will be implemented. This idea may have been generated before classes began, caused by previous experiences with a similar content, or be based on the information students already have about the teacher, etc. It may also arise on the first days of class when they meet the teacher and find out about the study syllabus, evaluation requirements, how the teacher is going to conduct the class, etc. Students now have sufficient information to enable them to answer four important implicit questions deriving from the motivational theory proposed by Pintrich (1989), Pintrich and De Groot (1990), and from the Expectancy-Value Theory proposed by Feather (1982) and Vroom (1964): a) Will I be successful in this subject? b) What value has this subject for me? c) How will I feel studying this subject, and d) How much time and effort will I devote to studying this subject according to the value it has for me? This same process similarly occurs with the teacher, but is not considered in this study.
The interactive involvement phase (Block 4) refers to the way that the teacher and students interact though a specific curricular content; that is to say, everything the teacher does to teach and everything students do to learn that particular content. The degree of teacher and student involvement in this phase and the degree of their interrelationship will depend on the expectations generated by them in the previous phase (the initial positioning phase). The present study centered on what students do to avoid learning, specifically on the avoidance learning strategies they used during the teaching/learning process undertaken in Educational Psychology. Previous motivational research has suggested that work avoidance in the school context is an academic goal in which students seem to make little effort to understand or complete academic tasks (Jarvis and Seifert, 2002, Seifert and O'Keefe, 2001). Seifert and O'Keefe (2001) indicated that students tend to avoid effort or minimize the amount of work they do at school for three major reasons: feeling of competence, boredom and lack of control. Students who perceive little control or competence seek to avoid effort because they believe they cannot do the work, or because they want to feel protected from the humiliation and shame associated with failure (Covington, 1984). Moreover, the students who perceive themselves capable of doing a task, but do not see any reason for doing it (for instance, because they find that the task is meaningless), also try to avoid making efforts in their learning process (Seifert & O'Keefe, 2001). Sloan (2007) found that motivational traits are one of the major reasons that teachers used to explain why students avoid work. Finally, attendance in classroom sessions of the Educational Psychology subject matter was also taken into account since it can be understood as a kind of avoidance strategy.
The main aim of this study was to examine the process which explains why undergraduate students employ avoidance learning strategies. Based on the aforementioned rationale, the hypothesized connections have been addressed and tested simultaneously using the Structural Equation Modeling (SEM) procedure. The causal model presented (see Fig. 2) has been designed in accordance with the configuration of the MCSE displayed in Fig. 1. As seen in the hypothesized model, the following predictions have been addressed. First, personal variables (from Block 1, the input phase) such as Prior knowledge, Interest in the subject, General Academic Self-Efficacy, Formative scope of the subject, General Self-Esteem, were expected to be good predictors of the students' initial motivation or intention to learn at the beginning of the T/L process (from Block 3, the preprocess phase) in Educational Psychology. Second, the students' initial motivation (from Block 3, the preprocess phase) was expected to be a good predictor of avoidance strategies and classroom attendance (from Block 4, the process phase).
Section snippets
Participants and procedure
The sample consisted of 195 psychology students, of whom 159 were female (81.5%) and 36 male (18.5%), who were aged between 20 and 47 years old (M: 22.78, SD: 3.83). The participants studied Educational Psychology during the 2010–11 and 2011–12 academic years at the Universitat Jaume I, Castellón (East Spain). Educational Psychology is an annual core subject and is taught in the third year of the Psychology degree.
The study was carried out during two consecutive academic years in the Educational
Descriptive statistics and internal consistency of scales
The mean, standard deviation, reliability, structure of the scales and item examples are shown in Table 1. In general, the factorial analyses performed confirmed the scales' original structure and configuration. Cronbach's alpha coefficients indicated good internal consistency for all the scales with a 0.71 to 0.94 range. See Table 1 for more details.
Correlation between variables
A bivariate correlational analysis was carried out as an approach to explore the relationships between input (students' personal variables),
Discussion and conclusions
The hypothesized connections shown in the Model presented (Fig. 2) have been examined simultaneously to explore the system of relationships. It was expected that, first, personal variables would be good predictors of students' initial motivation or intention to learn (measured through MPV at the beginning of the T/L process); and second, students' initial motivation would be good predictors of Avoidance strategies and Classroom attendance in Educational Psychology. The results are discussed
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