Instructional Psychology Research Paper

The question whether the tremendous amount of research in instructional psychology over the past decades has contributed to better educational practices remains controversial. In this respect the distinction between a disciplinary vs. an educational orientation in educational/instructional psychology is relevant. In the first case, instructional psychology is considered as an offshoot of psychology which mainly aims at contributing to the development of theory and methodology within the broader domain of the mother discipline. In the second case, the focus is rather on acquiring a better understanding of education as a basis for the improvement of educational practices. The disciplinary orientation has dominated for a large part of the twentieth century, especially during the associationist and behaviorist era in psychology. The prevailing type of research were laboratory studies characterized by a great concern for internal validity, and, thus, including a high degree of experimental precision. But this way of conducting research easily overlooked educationally important aspects, and has therefore been often criticized for its lack of classroom relevance. Whereas the discipline approach is certainly still alive today, the educational orientation in instructional psychology has gained more and more ground since the 1970s, and has by now resulted in an empirically underpinned knowledge base that can guide the analysis of teaching practices, but also the design of new, powerful learning environments.

A comprehensive review of this extensive field of research is outside the scope of this research paper. Snow and Swanson (1992) have distinguished five essential components in a theory of learning from instruction: (a) description of desired end states or goals of instruction in a domain; (b) description of goal-relevant initial states of learners prior to instruction; (c) explanation of the transition processes from initial to desired states; (d) specification of instructional conditions that promote this transition; and (e) assessment of performance and instructional effects. This research paper will focus selectively on three of these components, namely desired end states, transition processes, and instructional conditions. For a more thorough overview of the field, especially from an Anglo-Saxon perspective, the reader is referred to the series of review articles in the Annual Review of Psychology (especially those from 1981 on), and the first Handbook of Educational Psychology (Berliner and Calfee 1996). To get a more comprehensive idea of European research, one can consult the periodicals European Journal of Psychology of Education (published since 1986), and Learning and Instruction. The Journal of the European Association for Research on Learning and Instruction (published since 1991), and the volumes appearing in the series Advances in Learning and Instruction, recently begun to be published by Elsevier Science.

2. Toward A Dispositional View Of Competence As Desired End State

During the behaviorist era learning was a prominent issue in psychological research. But with the advent of cognitive science the focus shifted toward the analysis of the structures and processes of human competence in an attempt to answer questions concerning the representation and organization of knowledge, the nature and characteristics of understanding, and the knowledge and cognitive skills involved in competent problem solving. This work, resulting in the identification of critical aspects of expert performance, is relevant from an educational perspective, because it contributes to defining the primary goals of learning in different instructional and training settings. In this respect there is now a broad consensus that becoming skilled in a given domain requires the integrated acquisition of four categories of aptitudes (for a more detailed discussion see, e.g., De Corte 1995):

(a) a well-organized and flexibly accessible domainspecific knowledge base, that constitutes the substance of a subject-matter field;

(b) heuristic methods, i.e., search strategies for problem analysis that increase the probability of finding the right solution, because they induce a systematic approach to the problem;

(c) metacognition which involves knowledge and beliefs about one’s own cognitive functioning on the one hand, and skills and strategies for the self-regulation of one’s own cognitive processes on the other; and

(d) affective components such as beliefs, attitudes, and emotions relating to a subject-matter field.

In the early days of cognitive science, laboratory investigations using mainly knowledge-lean tasks showed the important role of general cognitive skills in skilled problem solving. But starting in the mid-1970s expert–novice studies in rich content domains demonstrated the significant role of domain-specific knowledge in expert performance. Yet continued research in the 1980s evidenced that domain-specific knowledge could not fully account for human expertise, and showed that metacognitive, self-regulatory skills are a major determinant of successful learning and skilled thinking. Nowadays most scholars endorse the viewpoint that ‘we should combine the learning of domainspecific subject matter with the learning of general thinking skills, while also making sure that children learn to monitor and control their thinking and learning’ (Bruer 1993, p. 52).

However, the available evidence shows that the integrated acquisition of domain-related knowledge and general cognitive skills is not yet sufficient to overcome the well-known phenomenon of inert knowledge. In other words, expert performance entails more than the sum of the different categories of aptitudes mentioned above; it requires in addition a disposition toward skilled learning, thinking, and problem solving. According to Perkins (1995), a disposition involves, besides ability and motivation, two other crucial components, namely sensitivity and inclination. Sensitivity refers to the feeling for problem situations in which it is relevant and useful to apply acquired knowledge and skills, while inclination is the tendency to do so whenever appropriate. This dispositional conception of expertise accounts for the phenomenon of inert knowledge: students often possess the ability to perform certain tasks or to solve problems, but do not exercise them because of lack of spontaneous inclination and sensitivity.

Since the beginning of the 1990s it has been properly observed that due to the dominance of the information-processing approach, instructional psychology has studied cognition and learning too one-sidedly from a cognitive perspective. Therefore, researchers have begun to pay more attention to building connections between the affective, emotional, and motivational aspects of learning on the one hand, and the cognitive components on the other (see, e.g., Boekaerts 1992). In this respect the dispositional view of skilled learning and thinking offers a useful framework for the integration of both kinds of aptitudes, in the sense that the sensitivity and inclination aspects of the disposition can be conceived of as interfaces or mediators between the cognitive and the affective components.

Being able to transfer knowledge and skills to new learning tasks and problem situations is widely considered as an important goal of education. Therefore, it is not surprising that since the early days of instructional psychology, transfer has repeatedly been, and still is, the main focus of research on learning and instruction. The available literature shows that transfer is a very complex phenomenon, that transfer effects do not occur spontaneously, and that they are even difficult to obtain deliberately (see, e.g., De Corte 1999).

3. Constructive Learning As Lever For The Transition From Initial To Desired End State

Due to the emphasis of cognitive psychological research on the analysis of performance, the study of learning was largely unpopular in the early days of the information-processing approach. But the scene has changed since then, and many researchers working in the cognitive tradition show an active interest in learning processes. Moreover, their work has been enriched by contributions from research on learning in nonschool settings, especially anthropological studies of apprenticeships. From this research a series of characteristics of effective and meaningful learning processes has emerged, which can be summarized in the following definition of learning: it is a constructive, cumulative, self-regulated, goal-directed, situated, collaborative, and individually different process of meaning construction and knowledge building. Only some of these characteristics can be briefly elaborated here (see De Corte 1995 for a more detailed discussion).

3.1 Learning Is Constructive

Research has shown that learning is an effortful and mindful process, in which students actively construct knowledge and skills through reorganization of their already acquired mental structures in interaction with the environment. Some scholars—often inspired by the work of Piaget (1955)—take a radical position in this respect, claiming that all knowledge is a subjective and idiosyncratic cognitive construction; others represent a more moderate point of view that allows for the possibility of mediating learning through appropriate guidance. Notwithstanding the large variety in theoretical perspectives along the radical–moderate dimension, the constructivist view certainly implies that acquiring knowledge and skills requires active cognitive processing from the learner.

3.2 Learning Is Self-Regulated

This feature refers to the metacognitive nature of effective learning, and is implied in the constructive perspective. Indeed, self-regulation means that students manage and monitor their own processes of knowledge building (Schunk and Zimmerman 1998). Skilled self-regulation facilitates appropriate decision making during learning, as well as the monitoring of an ongoing learning process by providing one’s own feedback and performance evaluations, and by keeping oneself concentrated and motivated. The more students become self-regulated, the more they assume agency over their learning; consequently they are less dependent on external, instructional support for performing those regulatory activities. An additional argument for promoting students’ self-regulation of their learning derives from the finding that high levels of metacognition facilitate transfer: students having good metacognitive awareness and strategies are more able at using what they have learned to approach unfamiliar problems in multiple ways (Brown 1989).

3.3 Learning Is Situated And Collaborative

The conception that learning and cognition are situated emerged in the 1980s in reaction to the then prevailing mentalistic, information-processing view of learning and thinking as highly individual and purely cognitive processes occurring in the head, and resulting in the construction of mental representations. In contrast, situativity theory—influenced by the work of Vygotsky (1978)—proposes a contextualized and social conception of learning and thinking: learning is enacted essentially in interaction with the social and cultural context and artifacts, and especially through participation in cultural activities and contexts (Brown et al. 1989). In other words, effective learning is not a purely ‘solo’ activity, but essentially a distributed one, i.e., the learning effort is distributed over the individual students, their partners in the learning environment, and the resources and tools that are available. Thus, this situated perspective strongly stresses the importance of collaboration in productive learning reflected in such activities as exchanging ideas, comparing solution strategies, and discussing arguments.

4. Powerful Teaching–Learning Environments To Promote Transition To The Desired End State

Powerful teaching–learning environments create the appropriate instructional conditions to evoke in students the learning processes that facilitate transition from their initial state toward the disposition to productive learning, thinking, and problem solving. Therefore, a challenging task for instructional psychology research consists of elaborating and validating a coherent framework of principles for the design of such powerful learning environments. Starting from our current knowledge and understanding of skilled performance in a variety of content domains (as described in Sect. 2) and of the characteristics of effective acquisition processes (see Sect. 3), but also based on observation of the practice of excellent teachers, researchers have begun to address this challenge over the past few years. A promising approach in this respect consists in the creation and evaluation in real classrooms of complex and fundamentally new instructional interventions guided by design principles that embody this present understanding of competence, of effective learning processes, and of successful teaching. Major examples of such orienting principles for the design of powerful learning environments are the following (De Corte 1995):

(a) Learning environments should initiate and support constructive and self-regulated acquisition processes in all students, thus also including the more passive learners. However, from a moderate constructivist perspective, students’ construction of knowledge can be mediated through appropriate guidance by teachers, peers, and educational media. In other words, the claim that productive learning requires good teaching still holds true. But, this first principle also implies that systematic interventions should gradually be removed, so that students progressively become agents of their own learning.

(b) Complementary to the first principle, learning environments should allow for the flexible adaptation of instructional support, especially the balance be-tween self-regulation and external regulation, to take into account individual differences in cognitive as well as in affective and motivational aptitudes. Moreover, the crucial influence on learning of motivational factors points to the necessity of balancing instructional interventions and affective support (Boekaerts 1992).

(c) Taking into account the situated and collaborative nature of effective learning, powerful learning environments should embed students’ constructive acquisition processes as much as possible in real-life contexts that have personal meaning for the learners, that offer ample opportunities for distributed learning through social interaction and cooperation, and that are representative of the tasks to which students will have to apply their knowledge and skills in the future. Acquisition of a disposition to skilled learning and thinking, especially the inclination and sensitivity aspects of this disposition, will require extensive experience and practice with the different aptitudes involved, in a large variety of situations.

(d) Because domain-specific knowledge and do-main-general heuristic and metacognitive strategies play a complementary role in competent learning and problem solving, learning environments should create opportunities to acquire general cognitive skills embedded in different subject-matter domains.

Cognitive apprenticeship (Collins et al. 1989) is a model for the design of innovative learning environments that is largely in accordance with those principles. The model describes four dimensions that constitute a learning environment: content, teaching methods, sequence of learning tasks, and social con- text of learning. With respect to content, an ideal learning environment should focus on the acquisition of all categories of knowledge that experts master, namely domain-specific knowledge, heuristic methods, metacognitive skills, and learning strategies. To help students to acquire those different categories of knowledge and skills, the teacher can apply six different teaching methods: modeling, coaching, scaffolding, articulation, reflection, and exploration. The model specifies three principles for sequencing the learning tasks: increasing complexity, increasing diversity, and performing global before local skills. Finally, five guidelines are given for creating a favorable social context for learning: situated learning, opportunities for observation of experts, enhancing intrinsic motivation, fostering cooperative learning, and comparing problem-solving processes and strategies.

Although further research is needed to validate the design principles described above, a series of intervention studies in a variety of content domains that embody those guidelines to some degree have already reported supporting empirical evidence. Often these investigations also integrate educational technology, especially computer programs and, more recently, multimedia systems, in their learning environments. One of the most representative examples of such a research-based attempt at totally changing the classroom environment is the Schools for Thought project in the USA (Lamon et al. 1996).

5. Conclusion

This selective, and thus incomplete, review shows that in the 1980s and 1990s research in the field of instructional psychology made substantial progress toward the elaboration of a theory of learning from instruction. Indeed, we now have a fairly good understanding of what skilled performance in a large variety of content domains involves. At the same time the research in which performance of experts and novices was contrasted has contributed to the clarification of one of the components of a theory of learning from instruction that was not explicitly addressed in this research paper, namely the description of goal-relevant initial states of learners prior to instruction. Considerable advances have also been made in unraveling major characteristics of effective learning processes. And a series of intervention studies has started to address basic questions relating to the design and evaluation of powerful teaching–learning environments to elicit and maintain acquisition processes that are conducive to the attainment of a disposition to competent learning, thinking, and problem solving.

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