New Developments in the Field of Self-Regulated Learning
This special issue offers some examples for the state of the art in the field of research on self-regulation. It includes the development of new instruments to assess relevant aspects of self-regulation, the prediction of self-regulation strategy use, the efficient improvement of self-regulated learning, the integration of self-regulated learning in everyday school life, and the validation of a process approach to self-regulation.
Self-regulation represents the essential capability of living organisms to adapt to the requirements of different and changing environments (Zimmerman, 2000; Baumeister & Vohs, 2004). These aspects become increasingly important because the demands of the environment and, thus, the demands on individuals, change rapidly and continually.
For example, people have to deal with an increasing amount of knowledge. Also, the results of the OECD Program of International Student Assessment (PISA) pointed out the importance of the growing use of self-regulation strategies (see e.g., Ertl, 2006). In school as well as in professional life, but also in everyday life, it is necessary to be able to continuously acquire new knowledge or adapt already existing knowledge to new requirements. In this regard, self-regulation is becoming increasingly important for academic learning as well as for vocational development and professional careers.
Systematic research on self-regulation began in the mid-1980s, mainly in the areas of social psychology and personality psychology. In the 1990s, publications began to appear in educational, organizational, clinical, and health psychology journals (see Boekaerts, Pintrich, & Zeidner, 2000). In the meantime, research was able to prove that self-regulation is important in many different fields of psychology, such as health behavior, vocational development, learning and education (e.g., Boekaerts, Maes, & Karoly, 2005; Frayne & Geringer, 2000; Schwarzer, Scholz, Lippke, Sniehotta, & Ziegelmann, 2006; Schunk & Zimmerman, 1998; Schmitz & Wiese, 2006). It was shown that self-regulation is important throughout the whole life span and can be used in a great variety of areas of life including attention disorders, emotion-regulation, writing, and vocational goal attainment (e.g., Barkley, 2004; Latham & Frayne, 1989; Larsen & Prizmic, 2004; Leutner & Leopold, 2006; Zimmerman & Kitsantas, 1997). Depending on the specific focus, various partly overlapping models of self-regulated learning are available.
Self-regulation is originally based on a system-theoretic concept of regulation (Wiener, 1948). This technical model can be transferred to human behavior. In the system-theoretic model a desired value is compared with the actual value. In case of deviations, regulation becomes necessary. Based on this basic assumption, Bandura (1986) described goals (desired values), acting, identification of the actual value (monitoring), and regulation as essential aspects of self-regulation. In line with Bandura, Zimmerman developed a frequently used model of self-regulation that describes the process of self-regulation as a sequence of the three phases (1) planning, (2) acting and volitional control, and (3) self-reflection (e.g., Zimmerman, 2000; Zimmerman & Kitsantas, 2007). Central characteristics of the model are feedback loops and the inclusion of motivational and emotional components. It differs from other models of self-regulation that focus primarily on the cognitive perspective.
Winne (1996) accents the metacognitive perspective. He defined self-regulated learning as a metacognitively-governed behavior where learners regulate their use of cognitive tactics and strategies. Another distinction between models of self-regulation is the postulated influence of the situation on self-regulation behavior. Winne and Perry (2000), for example, consider self-regulation as a personal trait. Other authors like Schmitz (2001) focus on how the situation influences self-regulation.
Boekaerts (1997) defines self-regulated learning as a complex interaction between (meta)cognitive and motivational regulation. She developed a model consisting of six components, by differentiating both regulation systems in relation to three levels (goals, knowledge, and cognitive strategies). In the model of adaptable learning in the classroom (Boekaerts, 1992), not only the learning process but also the learner him or herself becomes the object of regulation. The internal processing of three kinds of information (learning situation, domain-specific metacognitive knowledge, and self-system) leads to positively or negatively charged assessment. Depending on the quality of the appraisal, the learners want to extend their knowledge and skills (positive appraisal) or intend to protect their ego and prevent themselves from loss of resources and well-being (negative appraisal). In this approach, adaptable, self-regulated learning is defined as the balance between these two paths. Boekaerts and Niemivirta (2000) emphasize the uniqueness of the assessment of each learning situation and both optimal and nonoptimal conditions for self-regulated learning.
Leutner and Leopold (2006) made a further distinction between different kinds of self-regulation. They referred to metacognitive aspects of self-regulation and differentiated a general from a specific level of learning-process monitoring. The general level of monitoring is goal-oriented and aims at the final result of the learning process. In contrast, the specific processes operate at a deeper level and focus on the adequate and correct use of certain learning strategies.
Currently, much domain-specific research is done using specific terminology, with regard to specific aspects of self-regulation. The present challenge mainly refers to the integration of the domain-specific approaches and models. More than 2,700 references could be found for the term “self-regulation” in the data base of the American Psychological Association (PsychINFO). For the terms “self-regulation” and “learning” there have been more than 700 entries since the year 2000, which indicates a great amount of research activity in the domain of self-regulated learning.
An essential aspect of research in the field of self-regulation is the assessment of self-regulation behavior. Questionnaires on the basis of self-reported data are most often used. Well-known examples are the Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich, Smith, Garcia, & McKeachie, 1993), or the Learning and Study Strategies Inventory (LASSI; Weinstein, 1988). Another possibility is to interview people regarding self-regulated learning (e.g., Self-Regulated Learning Interview Schedule [SRLIS]; Zimmerman & Martinez-Pons, 1988). Furthermore, self-regulated learning can be measured by the thinking aloud technique. This method is particularly appropriate for measuring cognitive and metacognitive strategies (e.g., Bannert, 2005; Garner, 1988). Finally, learning diaries as a state assessment tool allow the continuous collection of data during the self-regulation process. Additionally, learning diaries encourage the learners' self-reflection and self-regulation behavior (see e.g., Landmann, Pöhnl, & Schmitz, 2005; Schmitz, 2006; Spinath, 2005).
The first article in the present issue aimed at the validation of new instruments in self-regulation. Zimmerman and Kitsantas (2007) have developed an instrument for measuring self-efficacy beliefs about the use of self-regulatory strategies in various areas of academic involvement: the Self-Efficacy for Learning Form (SELF). It was developed as a measure of students' certainty on overcoming obstacles in academic learning. In addition to the long version of the SELF, a shortened version (SELF-A) was developed. The predictive validity of the scores on the SELF-A were found to be superior to the unabridged SELF for most variables (e.g., grade in an educational psychology course, the quality and quantity of homework, teacher ratings). The authors argued that the scores on either version of the SELF could be helpful for educators, because they are significant predictors for many important aspects of teaching and education. They recommend that teachers study the use of the SELF-A to guide classroom instruction in future research.
In the second article in this issue, Boekaerts and Rozendaal (2007) illustrate the complexity of predicting metacognitive self-regulation strategy use in the context of writing. The study tested whether variables related to beliefs about writing (here capacity, context beliefs, instrumentality of writing for goal attainment) contribute to the self-reported use of metacognitive strategies and whether the strategies were used in a genre-specific way. Moreover, gender-specific differences were predicted. The hypotheses were tested with students in secondary vocational education with the three different writing genres email, term paper, and application letter. It was found that capacity and context beliefs predicted metacognitive strategy use in the three genres. A view that writing is instrumental for the attainment of prominent personal goals (here well-being goals, mastery goals, or career goals) predicts the strategy use in a genre-specific way. Regarding gender differences, there was a trend for females to report more effective metacognitive strategy use. Moreover, genre interacted significantly with gender in relation to students' capacity beliefs. These results signal the complexity of predicting self-regulated metacognitive strategy use. Furthermore, this study indicates the importance of considering gender differences with regard to writing beliefs and personal goals.
The third contribution, by Leutner, Leopold, and den Elzen-Rump (2007), demonstrates the improvement of self-regulation competencies. The authors focused on learning strategies. They examined whether learners draw an additional benefit from the training of cognitive learning strategies (in this case text-highlighting) in combination with training of metacognitive strategies (in this case the regulation and goal-related application of the trained strategies). The authors developed a computer-based training to encourage the students to use the text-highlighting learning strategy. The comparison of the two groups with and without additional regulation strategies showed significantly better application of the text-highlighting strategy for the combined group when reading and processing a text. Interestingly, there was no difference in the self-reported strategy use. The results confirm earlier findings (Klauer, 2000), which point out the need for training on how to monitor and regulate the use of specific cognitive learning strategies. Additionally, the results direct attention to the limitation of the validity of instruments regarding the self-reported use of self-regulation strategies.
The fourth article in this issue from Schober, Finsterwald, Wagner, Lüftenegger, Aysner, and Spiel (2007) also focuses on the relevance of improving competencies in self-regulated learning, but in the context of lifelong learning. The authors present a comprehensive intervention program (TALK) for secondary school teachers. The TALK program is aimed at improving teacher competency for supporting pupils' competencies that are necessary for lifelong learning. Self-regulated learning and motivation are seen as the core competencies for lifelong learning as well as social skills and cognitive competencies. At the moment, 40 teachers are taking part in the pilot phase of this program, which ends in February 2008 and is embedded in an extensive evaluation study. Preliminary evaluative results show that participants benefit from the TALK program.
In the fifth and final part of the present issue, Perels, Otto, Landmann, Hertel, and Schmitz (2007) present a process model of self-regulation (Schmitz & Wiese, 2006) that provides a basis for several interventions in school settings. They verify the model assumptions with the help of state variables of self-regulation, which were measured by a standardized diary over a period of 49 days. Multivariate time-series analyses as well as synchronous and asynchronous correlations were calculated. The results indicate that the variables of the preaction phase influence the parameters of both the action phase and the postaction phase. Moreover, the results show that the parameters of the postaction phase have a significant influence on the parameters of the preaction phase in the following learning state. This supports the assumption of a cumulative learning process. Additionally, referring to the improvement of self-regulated learning, the authors of this article present a self-regulation intervention with 8th-grade students as a case study (see also Perels, Gürtler, & Schmitz, 2005).
Of course the studies presented in this special issue represent only an excerpt of self-regulation and self-regulated learning, but we believe that some relevant research aspects in the field of self-regulated learning have been addressed in this issue. We hope we were able to stimulate further research on self-regulated learning.
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