The impact of learner metacognition and goal orientation on problem-solving in a serious game environment

To understand the impact of two learner characteristics—metacognition and goal orientation—on problem-solving, this study investigated 159 undergraduate learners’ metacognition, goal orientations, and problem-solving performances and processes in a laboratory setting using a Serious Game (SG) environment—Alien Rescue (AR)—that adopts Problem-based Learning (PBL) pedagogy for teaching space science. Utilizing multiple data sources, including computer log data and problem-solving solution scores within the SG, survey data, gameplay screencast videos, and interview data, this study combined a sequential mixed method design and serious games analytics techniques to answer the following two questions: (a) To what extent are learner problem-solving performance differences based on learner characteristics, and why? (b) To what extent are learner problem-solving process differences based on learner characteristics, and why? The results indicated that (a) learner metacognition affected problem-solving. Specifically, there were statistically significant differences in learner problem-solving performances based on metacognition, and learners also demonstrated different problem-solving processes based on metacognition. (b) Learner goal orientation impacted problem-solving. Particularly, learners in different goal orientation groups had different problem-solving processes. (c) The interaction between metacognition and goal orientations had an impact on learner problem-solving performances. Specifically, learners were clustered into three groups based on these two characteristics, including (a) high metacognition and high multiple goal orientations, (b) low metacognition and medium multiple goal orientations, and (c) medium metacognition and low multiple goal orientations. Learner problem-solving performances were statistically significant based on these three clusters. In addition, learner metacognition and goal orientations together could predict learner problem-solving performances. (d) The interaction between metacognition and goal orientations also had an impact on learner problem-solving processes. These differences in learner problem-solving performances and processes can be explained by learner characteristic differences, the problem complexity, SG design, and Dunning-Kruger effects (i.e., the cognitive bias that people of low metacognitive ability might mistakenly assess their metacognitive level as higher than it is). In addition, this study summarized 10 steps of how to be a successful and efficient problem solver in AR. These steps are as follows: 1) identify the problem correctly; 2) explore the 3D environment by visiting all rooms in AR and look over all tools; 3) discover what one alien species needs to survive in Alien Database; 4) search the Solar System Database for possible planets; 5) develop hypotheses about where this alien species can live; 6) figure out if there is any missing information needed for making a decision; 7) launch probes to gather information in the Probe Design room; 8) check the data from the probe in the Mission Control room; 9) decide whether the selected planet is a good choice for the selected alien species; 10) if so, write a recommendation message with the justification in the Communication Center—if not, go back to step 4. This research offers additional understanding of learner characteristic impacts on problem-solving in SG environments with PBL pedagogy. It can also contribute to future designs of these environments to benefit learners based on their metacognitive levels. In addition, the study limitations and further research in this area are discussed.Curriculum and Instructio

Towards a Framework for Metacognition in Game-Based Learning

\u3cp\u3eGame-based learning can motivate learners and help them to acquire new knowledge in an active way. However, it is not always clear for learners how to learn effectively and efficiently within game-based learning environments. As metacognition comprises the knowledge and skills that learners employ to plan, monitor, regulate, and evaluate their learning, it plays a key role in improving their learning in general. Thus, if we want learners to become better at learning through game-based learning, we need to investigate how metacognition can be integrated into the design of game-based learning environments. In this paper we introduce a framework that aids designers and researchers to formally specify the design of game-based learning environments encouraging metacognition. With a more formal specification of the metacognitive objectives and the way the training design and game design aims to achieve these goals, we can learn more through analysing and comparing different approaches. The framework consists of design dimensions regarding metacognitive outcomes, metacognitive training, and metacognitive game design. Each design dimension represents two opposing directions for the design of a game-based learning environment that are likely to affect the encouragement of metacognitive awareness within learners. As such, we introduce a formalised method to design, evaluate and compare games addressing metacognition, thus enabling both researchers and designers to create more effective games for learning in the future.\u3c/p\u3

Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

Modes and Mechanisms of Game-like Interventions in Intelligent Tutoring Systems

While games can be an innovative and a highly promising approach to education, creating effective educational games is a challenge. It requires effectively integrating educational content with game attributes and aligning cognitive and affective outcomes, which can be in conflict with each other. Intelligent Tutoring Systems (ITS), on the other hand, have proven to be effective learning environments that are conducive to strong learning outcomes. Direct comparisons between tutoring systems and educational games have found digital tutors to be more effective at producing learning gains. However, tutoring systems have had difficulties in maintaining students€™ interest and engagement for long periods of time, which limits their ability to generate learning in the long-term. Given the complementary benefits of games and digital tutors, there has been considerable effort to combine these two fields. This dissertation undertakes and analyzes three different ways of integrating Intelligent Tutoring Systems and digital games. We created three game-like systems with cognition, metacognition and affect as their primary target and mode of intervention. Monkey\u27s Revenge is a game-like math tutor that offers cognitive tutoring in a game-like environment. The Learning Dashboard is a game-like metacognitive support tool for students using Mathspring, an ITS. Mosaic comprises a series of mini-math games that pop-up within Mathspring to enhance students\u27 affect. The methodology consisted of multiple randomized controlled studies ran to evaluate each of these three interventions, attempting to understand their effect on students€™ performance, affect and perception of the intervention and the system that embeds it. Further, we used causal modeling to further explore mechanisms of action, the inter-relationships between student€™s incoming characteristics and predispositions, their mechanisms of interaction with the tutor, and the ultimate learning outcomes and perceptions of the learning experience

Reflections on the Ecolab and the Zone of Proximal Development

In 1999 we reported a study that explored the way that Vygotsky’s Zone of Proximal Development could be used to inform the design of an Interactive Learning Environment called the Ecolab. Two aspects of this work have subsequently been used for further research. Firstly, there is the interpretation of the ZPD and its associated theory that was used to operationalize the ZPD so that it could be implemented in software. This interpretation has informed further research about how one can model context and its impact on learning, which has produced a design framework that has been successfully applied across a range of educational settings. Secondly, there is the Ecolab software itself. The software has been adapted into a variety of versions that have supported explorations into how to scaffold learners’ metacognition, how to scaffold learners’ motivation and the implications of a learner’s goal orientation upon their use of the software. The findings from these studies have informed our understanding of learner scaffolding and have produced consistent results to demonstrate the importance of providing learners with appropriately challenging tasks and flexible support. Vygotsky’s work is as relevant now as it was in 1999: it still has an important role to play in the development of educational software

A Mixed Method Study: Assessing Critical Thinking, Metacognition, and Motivation in a Flipped Classroom Instructional Model

Technology has changed pedagogical methods in higher education. Educators are using technology more and integrating more active learning techniques. One pedagogical method, the flipped classroom, is suitable for integrating technology and active learning techniques. The pedagogical efficacy of the flipped classroom has not been determined despite being a potential solution for technology savvy millennial students. This mixed method study assessed critical thinking, metacognition, and motivation in higher education flipped classrooms in the United States. Human Anatomy and Physiology Society (HAPS) members teaching traditional and flipped format science courses were purposefully selected to participate in the study. A sample of 14 HAPS educators recruited 426 students enrolled in their science courses to complete the Motivated Strategies for Learning Questionnaire (MSLQ), a five-point Likert scale instrument used to measure critical thinking, metacognition, and motivation. The study was a pre-test/post-test non-equivalent control group design with semi-structured interviews for flipped classroom educators. The MSLQ was administered at the beginning and end of the fall semester (16 weeks) or the summer semester (8 weeks). A multivariate analysis of variance was used to estimate relationships between classroom format (flipped or traditional) and outcome variables (critical thinking, metacognition and motivation). The results were not statistically significant, meaning the flipped classroom was not more effective than the traditional classroom format for the outcome variables. The semi-structured interviews with flipped classroom instructors addressed the limitations and challenges of implementing a flipped classroom instructional model (FCIM). The most common limitations and challenges were preparation, in-class activities, student attitudes, and classroom space. The findings from this study will help those making pedagogical decisions in higher education as well as educators interested in implementing FCIM

Culture, cognition and uncertainty: metacognition in the learning and teaching of probability theory

A Research Report submitted to the Faculty of Education, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Education by course-work and research report. Johannesburg, 1992This research report investigates the psychological dimensions in the learning and teaching of probability theory. It begins by outlining some problems arising from the author's own experience in the learning and teaching of probability theory, and develops a theoretical position using the Theory of Activity. This theory places education within the broad social context and recognises the centrality of affective aspects of cognition. [Abbreviated abstract. Open document to view full version

Multimodal teaching, learning and training in virtual reality: a review and case study

It is becoming increasingly prevalent in digital learning research to encompass an array of different meanings, spaces, processes, and teaching strategies for discerning a global perspective on constructing the student learning experience. Multimodality is an emergent phenomenon that may influence how digital learning is designed, especially when employed in highly interactive and immersive learning environments such as Virtual Reality (VR). VR environments may aid students' efforts to be active learners through consciously attending to, and reflecting on, critique leveraging reflexivity and novel meaning-making most likely to lead to a conceptual change. This paper employs eleven industrial case-studies to highlight the application of multimodal VR-based teaching and training as a pedagogically rich strategy that may be designed, mapped and visualized through distinct VR-design elements and features. The outcomes of the use cases contribute to discern in-VR multimodal teaching as an emerging discourse that couples system design-based paradigms with embodied, situated and reflective praxis in spatial, emotional and temporal VR learning environments

A Meta-Analysis of Self-Regulated Learning Interventions and Learning Outcomes in Higher Education E-Learning Environments

Through a systematic review of the literature, 36 empirical studies regarding self-regulated learning (SRL) interventions and learning outcomes in higher education e-learning environments were identified and meta-analyzed using15 years of data. Frequently studied interventions included providing SRL scaffolding, SRL training, or SRL training and scaffolding either as a precursor or as part of the learning environment or both. Scaffolding interventions were embedded as part of the learning environment and designed to guide learners to perform cognitive and metacognitive strategies such as task analysis, goal setting, and reflection during a learning activity. Training interventions, by contrast, involved instruction in the use of SRL strategies prior to beginning a learning activity, course or program. In some studies, both training and scaffolding SRL interventions were implemented. Information about the types of SRLinterventions including the means of measuring learning outcomes (more or less complex), instructional design characteristics and learning outcomes data for calculating effect sizes were extracted for the purposes of conducting this meta-analysis