Introduction
Changes in society during the late part of the 20th century have induced a growing need for the acquisition by all citizens of high literacy skills, such as thinking critically, solving complex problems, regulating one’s own learning, and having good communication skills. However, it has repeatedly been observed that education has not been able to keep up with these developments. For instance, in a report of the European Round Table of Industrialists (ERT) entitled Education for Europeans. Towards the Learning Society,1 an alarm was raised to alert society to the so-called educational gap, i.e. the fact that – due to its slowness in responding to changes in society – there is ‘an ever-widening gap between the education that people need for today’s complex world and the education they receive’ (Ref. 1, p. 6). This problem is even increasing because the pace of societal developments has recently accelerated dramatically due, among other things, to the exponential knowledge explosion, to globalization in many domains of society and to the large-scale introduction of the new information technologies. The same report puts forth the following characteristics of a learning society: learning is accepted as a continuous activity throughout life; learners assume responsibility for their own progress; assessment is designed to confirm progress rather than to sanction failure; personal competence and shared values and team spirit are recognized equally with the pursuit of knowledge; and learning is a partnership between students, teachers, parents, employers, and the community working together.
This vision of a learning society implies that education at all levels must focus more than has been traditionally the case on developing and fostering adaptive competence in students (i.e. the ability to apply meaningfully learned knowledge and skills, flexibly and creatively, in a variety of contexts), as opposed to routine expertise (i.e. the ability to complete typical school tasks quickly and accurately but without understanding).
This article will review and discuss the following themes:
∙ What should students learn to acquire adaptive competence in a domain?
∙ What are characteristics of productive and meaningful learning processes in view of acquiring adaptive competence?
∙ How can productive/meaningful learning processes be stimulated and kept going in students through instructional intervention? An illustrative powerful learning environment will be described.
∙ Final comments.
What should Students Learn? Acquiring Adaptive Competence as the Ultimate Goal of Learning and Teaching in a Content Domain
Developing adaptive competence in a domain requires the acquisition and mastery of several cognitive, affective, and motivational components:Reference De Corte2
(1) A well-organized and flexibly accessible domain-specific knowledge base, involving the facts, symbols, concepts, and rules that constitute the contents of a subject-matter field.
(2) Heuristic methods, i.e. search strategies for problem analysis and transformation that do not guarantee but significantly increase the probability of finding the correct solution through a systematic approach to the task. Examples are: decomposing a problem into sub-goals; making a graphic representation of a problem.
(3) Metaknowledge:
∙ Knowledge about one’s cognitive functioning (metacognitive knowledge), e.g. knowing the strengths and weaknesses of one’s cognitive capacities: knowing that one’s cognitive potential can be developed through learning and effort.
∙ Knowledge about one’s motivation and emotions that can be actively used to improve learning, e.g. becoming aware of one’s fear of failure in mathematics.
(4) Self-regulation skills
∙ Skills for regulating one’s cognitive processes/activities (cognitive self-regulation), e.g. planning and monitoring one’s problem-solving activities. Reflecting on a solution process.
∙ Skills for regulating one’s motivational and emotional processes (motivational self-regulation), e.g. maintaining attention and motivation to solve a given problem.
(5) Positive beliefs about oneself as a learner in general and in particular subject-matter fields (self-efficacy beliefs), about the classroom or the context in which learning takes place, and about the content of a subject-matter field.
Importance of Self-regulation
Successful learners and problem solvers can simultaneously perform two functions: executing a task, and organizing/evaluating (=self-regulating) the task-related activities by orienting oneself to the task, planning one’s approach to the task or problem, monitoring and evaluating the activities, and reflecting after a task has been performed.
Examples of cognitive self-regulating activities are:
∙ During text reading: a student regularly interrupts reading to ask him/herself whether his/her interpretation of the text is coherent and consistent.
∙ During text writing: a student re-reads from time to time his/her text to check the logic of the argumentation.
∙ During problem solving: a student realizes that he/she gets stuck. As a consequence the student says:
∙ let me read the problem again;
∙ did I overlook something in the problem statement?
∙ until what point did my solution process go well; where did I get in trouble?
∙ can I restructure the problem or consider it differently?
SchoenfeldReference Schoenfeld3 videotaped high-school and college students working in pairs on unfamiliar problems during 20-minute sessions, and contrasted the solution processes with those of experts.
Example of the problems used in this study:
‘Consider the set of all triangles whose perimeter is a fixed number P. Of these, which has the largest area? Justify your answer as best as you can.’
The solution processes were parsed into episodes representing different activities: reading the problem, analysing, exploring, planning, implementing, and verifying.
Time-line graphs were used to represent the course of the solution processes visually. The graphs illustrative of the novices’ solution process show how they read the problem, choose a certain approach and keep going with it, sometimes even when there was evidence that they were on the wrong track. This contrasts very strongly with the varied solution processes of experts who, after reading the problem, analysed it before planning the solution process. They followed this by verifying the plan, then returning to analyses, and so on.
Brown and CampioneReference Brown and Campione4 have shown that more successful learners are better self-regulators than less successful learners. It has also been demonstrated that self-regulation skills enhance the ability to transfer one’s knowledge and skills to new situations and problems.
Some Comments
Prioritizing adaptive competence does not mean that routine expertise becomes unimportant. It is obvious that mastering certain skills routinely (e.g. basic operations in arithmetic, spelling, reading, technical skills) is crucial to efficient functioning in all kinds of situations. If certain aspects of solving a complex problem can be performed more or less mechanically, it creates room to focus on the higher-order cognitive activities needed to reach a solution.
However, adaptive competence is so important because it goes beyond this: it involves the willingness and ability to change core competences and continually expand the breadth and depth of one’s expertise. Furthermore, it is fundamental, indeed necessary, to acquire the ability to transfer one’s knowledge and skills to new learning tasks and contexts.Reference Bransford, Stevens, Schwartz, Meltzoff, Pea, Roschelle, Vye, Kuhl, Bell, Barron, Reeves and Sabelli5 Hence, it follows that pursuing adaptive competence is central to lifelong learning.
Implications
Considering adaptive competence as a key goal has important implications for the kind of learning processes to best acquire it. The traditional dominant form of school learning has been teacher-directed or guided learning: a trainer or teacher takes all the relevant decisions and the learner can and should follow him or her.
Because an important component of adaptive competence consists of skills in self-regulating one’s own learning and thinking, it is obvious that such guided learning is certainly not the only appropriate way of learning to achieve it. Indeed, to support the acquisition of adaptive competence by students, novel classroom practices and cultures are needed that create the conditions for a substantial shift from guided learning towards more active and self-guided student learning, resulting in a balanced and integrated use of both these ways of learning. Such a balance allows for structure and guidance by the teacher where and when needed, and creates space for substantial self-regulated and self-determined learning by students.
What are the Characteristics of such Active Learning Processes needed to Facilitate and Support Students’ Acquisition of Adaptive Competence?
To realize the required shift, taking into account the importance of contextual and social factors impacting learning, school learning should embody more than was the case in the past, the characteristics summarized in the following definition:Reference De Corte6
it is an active/constructive, cumulative, self-regulated, goal-directed, situated, collaborative, and individually different process of meaning construction and knowledge building.
This article will focus on four key characteristics – Constructive, Self-regulated, Situated, and Collaborative (CSSC) – building thereby on students’ prior knowledge and taking into account individual differences. This CSSC view integrates the acquisition and participation metaphors of learning,Reference Sfard7 and the individual and social aspects of learning.Reference Salomon and Perkins8
Constructive
Learners are not passive recipients of information. Indeed, learning is always constructive, even in environments that embody a dominantly guided learning or direct instruction approach. This is well illustrated by the occurrence of misconceptions that students develop during teaching in many subject-matter domains, such as physics and mathematics, but also history. For instance, WineburgReference Wineburg9 has shown that many students develop misconceptions about history as being merely a collection of facts, and that learning history consists of passively accepting and absorbing factual information.
What is essential in the constructivist perspective on learning is the mindful and effortful involvement of students in the processes of knowledge and skills acquisition, in interaction with the environment.
Self-regulated
If students have to become life-long learners responsible for their own progress, they must be able to manage and monitor their processes of knowledge building and skill acquisition: i.e. they should become self-regulated learners. Skilled self-regulation facilitates the 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.
Research has identified the following major characteristics of self-regulated learners: they manage study time well; set higher specific and proximal goals; monitor more frequently and accurately; set a higher standard for satisfaction; are more self-efficacious; persist despite obstacles. It has also been shown in a variety of content domains that students’ degree of self-regulation correlates strongly with academic achievement.Reference Zimmerman and Risemberg10
It is very important from an educational perspective that recent meta-analyses of training studies show convincingly that self-regulatory processes can be enhanced in students through appropriate guidance.Reference Dignath and Büttner11 Self-regulation can therefore be conceived not only as a characteristic of productive learning but also as a goal of learning, and thus as a component of adaptive competence.
Situated or Contextual
Constructive and self-regulated learning processes should preferably occur in context, i.e. in relation to the social, contextual, and cultural environment in which these processes are embedded and that influence them, and through participation in cultural activities and contexts (for a thorough overview see Ref. Reference Kirschner and Whitson12).
Collaborative
The collaborative nature of learning is implied in the situated perspective that stresses the social character of learning: effective learning is not a purely ‘solo’ activity, but essentially a ‘distributed’ one, i.e. the learning efforts are distributed over the individual student, his partners in the learning environment, and the resources and tools (including technological ones) that are available
The literature provides substantial evidence supporting the positive effects of collaborative learning on academic achievement.Reference Slavin13 A shift toward more social interaction in classrooms would therefore represent a worthwhile move away from the traditional overemphasis on individual learning.
Parrying Challenges to Constructivist Approaches to Learning from Instruction
The constructivist perspective has recently been criticized, arguing that it focuses on pure discovery learning with minimal guidance, and ignores the structure of the human cognitive architecture in the sense that it imposes heavy loads on working memory.Reference Kirschner, Sweller and Clark14 Starting from these arguments, the critics plead in favour of direct instruction (see, for example, Ref. Reference Tobias and Duffy15).
However, these criticisms can be refuted on the basis of the currently available research literature. Whereas it is certainly correct that pure, unassisted discovery learning is not productive or effective, the critics mistakenly equate constructive learning with pure discovery learning. However, and to the contrary, constructive learning can be guided and mediated through appropriate interventions such as scaffolding, feedback, worked examples, technological tools and peer tutoring.
Based on a review of the relevant literature since 1960, MayerReference Mayer16 has come to the conclusion that such guided discovery yields better results than direct instruction. An extensive meta-analysis of the available researchReference Alfieri, Brooks, Aldrich and Tenenbaum17 confirms Mayer’s conclusions, stating that direct teaching is better than unassisted discovery, but that guided-, enhanced- or assisted-discovery learning is superior to direct or explicit teaching. But an important remark has to be added. Indeed, the amount of guidance/structure will vary depending on students’ prior knowledge as well as their achieved mastery level. In other words, the ratio between teacher guidance and student self-guidance will vary throughout students’ learning trajectory.
An example of an approach to teaching and learning that represents a form of implementation of a constructivist, guided-discovery method and that is today successfully used in higher education is so-called problem-based learning (see, for example, Ref. Reference Hmelo-Silver18).
How can CSSC Learning Processes be Stimulated and Kept Going in Students through Instructional Intervention? An Illustrative Powerful Learning Environment Focused on Fostering Self-regulation in University Freshmen
In the first part of the third millennium, higher education in Europe is facing several major problems, for example the need to adjust to larger and much more heterogeneous student populations, and the need for graduates who are prepared for lifelong learning. In response to these challenges we carried out a research project aimed at the design, implementation, and evaluation of a powerful learning environment for improving learning proficiency in students beginning university (for a more detailed report see Ref. Reference De Corte and Masui19). We took into account previous research and we made use of the growing knowledge base about self-regulated learning.
This article will discuss the following aspects of the study: theoretical and empirical background; blueprint of the instructional intervention; the quasi-experimental design; research question; measurement instruments; results and conclusions.
Theoretical and Empirical Background
We used the CLIA-model as a framework for designing a powerful learning environment.Reference De Corte, Verschaffel and Masui20
The model consists of four components:
∙ Competence: components of adaptive competence in a content domain.
∙ Learning: characteristics of effective learning processes.
∙ Intervention: principles and methods guiding the design of learning environments.
∙ Assessment: forms of assessment for monitoring and improving learning and teaching.
With respect to competence, the literature shows that metacognitive knowledge and a large variety of cognitive as well as affective-motivational self-regulation skills have an effect on students’ learning processes and outcomes. Research also reveals an intimate relationships between those skills Therefore, we opted for a multidimensional approach, i.e. a substantial number of regulatory activities were addressed in an integrated way in the learning environment.
Taking the research findings as well as the context of the present study into account, we first selected four cognitive self-regulation skills, namely orienting, planning, self-checking and reflecting.
∙ Orienting: preparing one’s learning process by examining the characteristics of the learning task.
∙ Planning: taking a series of decisions on how to approach the learning task.
∙ Self-checking: testing whether intermediate outcomes match the requirements of the intended learning goals.
∙ Reflecting: looking back to the learning process to draw conclusions about factors that influenced it.
Taking into account the interrelations between the cognitive and the affective-motivational domain we chose four matching affective-motivational skills:
∙ Since orienting implies evaluating one’s own weaknesses and strengths we firstly choose self-judging.
∙ We assumed that learning to plan was a good occasion to learn to make choices or to value.
∙ We included coping with emotions as the affective counterpart of self-checking.
∙ Finally reflecting seemed to provide sufficient reason for learning to attribute in a constructive way.
In this article, the description of the measurement instruments and the results will be restricted to two of the eight self-regulation skills, namely orienting and the affective counterpart self-judging.
Blueprint of the Instructional Intervention
The starting point for the development of the instructional intervention was that it should stimulate the following characteristics of effective learning: active, constructive, cumulative, goal-oriented, self-regulated, situated/contextualized, interactive, collaborative, individually different and transfer promoting.
Taking this into account, an integrated set of seven instructional principles guided the development of the intervention.
(1) Embed acquisition of knowledge and skills in the real study context, i.e. the selected activities have to be taught in the context in which students must apply them (situated learning).
(2) Take into account the study orientation of the students and their need to experience the usefulness of the learning and study tasks (personal usefulness).
(3) Sequence teaching methods and learning tasks and relate them to a time perspective (sequencing and time perspective).
(4) Use a variety of forms of organization and social interaction (variation in organization and social settings).
(5) Take into account informal prior knowledge and large differences between students (adjusting to prior knowledge).
(6) Stimulate the articulation of and reflection upon learning and thinking processes (verbalizing and reflecting).
(7) Create opportunities to practice and to transfer learned activities to new content domains (practice and transfer).
Quasi-experimental Design
The treatment of the experimental group (E) involving 47 students consisted of ten sessions of 90 minutes (two general sessions, three for macro-economics, five for management accounting), plus homework assignments aimed at practising and transferring knowledge and skills. The treatment focused on the eight regulatory skills.
The treatment of the first control group (C1) involving 47 students consisted of ten sessions plus homework, but the focus was not on regulatory but on cognitive skills, such as analysing, structuring, relating, rehearsing.
The second control group (C2) also involving 47 students received no special treatment, but participated in the regular practice seminars for macro-economics and management accounting.
Research Questions
(1) Do E-students have more detailed knowledge of the regulation activities (orienting and self-judging) after the intervention than the control students (C) do, and is there a positive relationship between this knowledge and academic performance?
(2) After the intervention are E-students better self-regulators, i.e. do they use more orienting and self-judging activities than C-students, and is there a positive relationship between regulation behaviour and academic performance?
(3) Are the study results of E-students better than those of C-students, and did the students consider the training effective?
Measurement Instruments
∙ Metacognitive knowledge: one week after the final intervention session, a knowledge test on metacognitive and affective-motivational activities was administered.
∙ Orienting and self-judging behaviour: we tried to find out whether students had become more proficient and self-regulated in learning, in the sense that they transferred the trained study activities to a course that was not involved in the intervention, more specifically statistics. Therefore, a questionnaire containing 11 questions about study activities and experiences in the statistics course was administered.
∙ Exam scores and study career data.
Results
The overall results of the intervention were quite positive (with effect sizes that are small to medium). This will be illustrated here with respect to orienting and self-judging.
Metaknowledge: the E-students had significantly more knowledge about orienting and self-judging than the students of the C-groups.
Metaknowledge and study result:
∙ The linear multiple regression of the study results of the E-students on the entering characteristics (e.g. prior knowledge, intelligence, cognitive study skills as measured before the intervention) equalled 0.65. In other words, these variables explain 43% of the criterion variance.
∙ After successively introducing knowledge of orienting and knowledge of self-judging in the regression equation variance explained rose from 43% to 47% and 50% respectively.
Regulation behaviour for statistics: there were significantly more indications of orienting and self-judging in E-group than in the C-groups.
Regulation behaviour and study result in statistics:
∙ The linear multiple regression of the study results for statistics of the E-students on the entering characteristics was 0.64. These variables explain thus 41% of the criterion variance.
∙ After including orienting behaviour and self-judging behaviour for statistics in the regression equation variance explained increased from 41% to 51% and 55% respectively.
This means that aspects of transfer behaviour, such as orienting and self-judging, matter with regard to academic performance.
Study results: Considering the study results in the first year (average percentage); the students of the E-group obtained significantly better overall study results than the C-groups, including for the two courses involved in the intervention, namely macro-economics and management accounting.
Considering the study career: significantly more E-students succeeded in the first year and got their degree.
In summary, the intervention resulted in the following positive effects in the E-group:
∙ More metaknowledge about learning activities.
∙ More self-regulation activities in the courses involved in the intervention.
∙ More control over academic performance.
∙ Significant transfer of self-regulating activities to a non-intervention course.
∙ Better academic performance as measured by exam scores, pass rates, and study careers.
Final comments
This example of a design experiment supports the view that the CSSC conception of learning as a constructive, situated/contextualized, collaborative, and progressively more self-regulated process can guide the design of novel, but also practically applicable, powerful learning environments, i.e. settings that facilitate in students the acquisition of adaptive competence, in this case self-regulation skills.
However, effective and sustained implementation of such novel learning environments puts great demands on teachers and requires drastic changes in their role and teaching practices. Instead of being the main source of information, the teacher becomes a ‘privileged’ member of a knowledge building community who creates an intellectually stimulating classroom climate; models learning, thinking, and problem-solving activities; asks provoking questions; provides support to learners through coaching and guidance; and fosters students’ self-regulation of their own learning. In other words, the teacher practises guided- or assisted-discovery learning.
Sustained large-scale innovation of higher education is a major challenge for educational leadership and policy makers, and is aimed at transferring research-based knowledge about learning and teaching to educational professionals and at guaranteeing its high-fidelity application in classrooms. An indispensable condition for success in this regard lies in the design and implementation of a well-grounded and well-elaborated system for initial and continued teacher professional learning and development, based on innovative ideas and practices. In this respect, research has shown that to make significant changes in their practices, teachers need time and multiple opportunities in a variety of activities (e.g. modelling and coaching of teaching practices) to learn new information and grasp its implications for classroom practice. In addition, teachers themselves need to develop self-regulation skills that will enable them to monitor and reflect on the effectiveness of changes they make to their practice; in other words, they have to become reflective practitioners.Reference Timperley21
Acknowledgements
This article is based on a paper presented in the Tsinghua University and Academia Europaea International Conference on ‘Humanities and Social Sciences, Globalization, and China’. Beijing, China, 15–17 May 2014.
Erik De Corte is Emeritus Professor (of Educational Psychology) in the Faculty of Psychology and Educational Sciences at the University of Leuven, Belgium where he chaired, from August 1994 until July 1998, the Department of Educational Sciences. His major research interest is to contribute to the development of theories of learning from instruction and the design of powerful learning environments, focusing thereby on learning, teaching, and assessment of thinking and problem solving. He was the first President (1985–1989) of the European Association for Research on Learning and Instruction (EARLI). Respectively in 2000 and 2003 he has been conferred the doctorate honoris causa of the University of Johannesburg, and the University of the Free State, Bloemfontein, South Africa. During the academic year 2005–2006 he stayed as a Fellow at the Center for Advanced Study in Behavioral Sciences at Stanford, USA. (http://perswww.kuleuven.be/~u0004455)
