Douglas B. Clark

Digital Games, Design, and Learning A Systematic Review and Meta-Analysis

In this meta-analysis, we systematically reviewed research on digital games and learning for K–16 students. We synthesized comparisons of game versus nongame conditions (i.e., media comparisons) and comparisons of augmented games versus standard game designs (i.e., value-added comparisons). We used random-effects meta-regression models with robust variance estimates to summarize overall effects and explore potential moderator effects. Results from media comparisons indicated that digital games significantly enhanced student learning relative to nongame conditions ( g ¯ = 0.33, 95% confidence interval [0.19, 0.48], k = 57, n = 209). Results from value-added comparisons indicated significant learning benefits associated with augmented game designs ( g ¯ = 0.34, 95% confidence interval [0.17, 0.51], k = 20, n = 40). Moderator analyses demonstrated that effects varied across various game mechanics characteristics, visual and narrative characteristics, and research quality characteristics. Taken together, the results highlight the affordances of games for learning as well as the key role of design beyond medium.

Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework

Computational thinking (CT) draws on concepts and practices that are fundamental to computing and computer science. It includes epistemic and representational practices, such as problem representation, abstraction, decomposition, simulation, verification, and prediction. However, these practices are also central to the development of expertise in scientific and mathematical disciplines. Recently, arguments have been made in favour of integrating CT and programming into the K-12 STEM curricula. In this paper, we first present a theoretical investigation of key issues that need to be considered for integrating CT into K-12 science topics by identifying the synergies between CT and scientific expertise using a particular genre of computation: agent-based computation. We then present a critical review of the literature in educational computing, and propose a set of guidelines for designing learning environments on science topics that can jointly foster the development of computational thinking with scientific expertise. This is followed by the description of a learning environment that supports CT through modeling and simulation to help middle school students learn physics and biology. We demonstrate the effectiveness of our system by discussing the results of a small study conducted in a middle school science classroom. Finally, we discuss the implications of our work for future research on developing CT-based science learning environments.

Exploring Newtonian mechanics in a conceptually-integrated digital game: Comparison of learning and affective outcomes for students in Taiwan and the United States

This study investigates the potential of a digital game that overlays popular game-play mechanics with formal physics representations and terminology to support explicit learning and exploration of Newtonian mechanics. The analysis compares test data, survey data, and observational data collected during implementations in Taiwan and the United States with students in grades 7-9. Results demonstrate learning on some core disciplinary measures and high levels of learner engagement, indicating the potential benefits of this genre of conceptually-integrated games, but also suggesting that further research and development will be needed to more fully harness this potential. Encouragingly, striking similarities were observed across the two countries in terms of learning and engagement, suggesting that this genre of learning games may prove suitable for engaging students in active exploration of core science concepts across multiple countries.

Integrating self-explanation functionality into a complex game environment: Keeping gaming in motion

Previous research has shown that either asking students to explain their answers or providing explanatory feedback can be effective ways to increase learning from an educational game. This study focused on an educational physics game about Newtons 3 Laws of Motion called SURGE: The Fuzzy Chronicles. Eighty-six middle school students played one of three versions of the game: (1) the base version with no tips or questions, (2) the self-explanation version with self-explanation questions prompts, and (3) the explanatory feedback version with gameplay tips. There were no significant overall learning differences between the three groups, but students in the base version successfully answered more questions about Newtons second law than students in the self-explanation group. This may have been due to students in the base condition progressing significantly further through the game than students in the self-explanation group. The results suggest that the cognitive load for gameplay as well as game flow must be managed in order for students to take advantage of explanation functionality in educational tools designed to increase deeper, germane processing.

Bilingual language supports in online science inquiry environments

Research over the past fifteen years has investigated and developed online science inquiry environments to support students engaging in authentic scientific inquiry practices. This research has focused on developing activity structures and tools to scaffold students in engaging in different aspects of these practices, but relatively little of this research has explored linguistic supports for language minority students studying science in their non-native language. These students are simultaneously learning science and the surrounding academic language in their second language. This study investigates the potential value of providing 8th grade Spanish-speaking English language learners access to content and supports in both English and Spanish as opposed to an English-only format in an online science inquiry environment. Learning outcomes are compared between the two conditions on an immediate post-test in English, a delayed post-test in English, a delayed post-test in Spanish, and a written essay in English in the form of a letter to the governor. The outcomes suggest significant benefits for providing ELL students with access to content and supports in both English and Spanish as opposed to the English-only format. The findings of this study carry important policy implications in light of the growing English-only political movements in the United States and similar political movements in other countries.

Digital games and the US National Research Council’s science proficiency goals

This review synthesises research on digital games and science learning as it supports the goals for science proficiency outlined in the report by the US National Research Council on science education reform. The review is organised in terms of these research-based goals for science proficiency in light of their alignment with current science education standards and reform documents worldwide. Overall, the review suggests that digital games can support science learning across the four strands but also suggests that there are few strong quantitative studies examining some of the strands. Much of the research conducted to date has centred primarily on the potential of games to scaffold conceptual knowledge, engagement and participation. Less research has focused on epistemological understanding and science process skills. While much debate has asked whether digital games are ‘good’ or ‘bad’ for learning, the research across the strands highlights that the design of digital games, rather than their medium, ultimately determines their efficacy for learning.

Identifying middle school students’ challenges in computational thinking-based science learning

Computational thinking (CT) parallels the core practices of science, technology, engineering, and mathematics (STEM) education and is believed to effectively support students’ learning of science and math concepts. However, despite the synergies between CT and STEM education, integrating the two to support synergistic learning remains an important challenge. Relatively, little is known about how a student’s conceptual understanding develops in such learning environments and the difficulties they face when learning with such integrated curricula. In this paper, we present a research study with CTSiM (Computational Thinking in Simulation and Modeling)—computational thinking-based learning environment for K-12 science, where students build and simulate computational models to study and gain an understanding of science processes. We investigate a set of core challenges (both computational and science domain related) that middle school students face when working with CTSiM, how these challenges evolve across different modeling activities, and the kinds of support provided by human observers that help students overcome these challenges. We identify four broad categories and 14 subcategories of challenges and show that the human-provided scaffolds help reduce the number of challenges students face over time. Finally, we discuss our plans to modify the CTSiM interfaces and embed scaffolding tools into CTSiM to help students overcome their various programming, modeling, and science-related challenges and thus gain a deeper understanding of the science concepts.

Driving Assessment of Students’ Explanations in Game Dialog Using Computer-Adaptive Testing and Hidden Markov Modeling

How might research on metacognition, conceptual change, and students’ explanations inform the design of dialog systems in digital games to foster science learning and engagement? How might research on computer-adaptive testing (CAT) and hidden Markov modeling support online diagnostic modeling of students’ learning behaviors and understanding? How might a game analyze their problem-solving steps as well as explanation constructs in that dialog? This chapter explores these questions. Our goals involve (1) scaffolding students’ explicit articulation of connections between intuitive understandings and disciplinary concepts in the game environment while (2) providing mechanisms for online tracking of players’ evolving understanding to support adaptive scaffolding and provide formative and summative diagnostic information to teachers and researchers. Essentially, we propose that integrating research on conceptual change, scientific explanations, metacognition, CAT, and hidden Markov modeling in a digital game environment could simultaneously diagnose the formative and summative aspects of students’ understanding, and in this process provide an environment that fosters deep science learning. We first define the challenge of scaffolding deep learning in games at the cognitive level by contrasting constraint-based reasoning and model-based reasoning. We then explore the role of self-explanation in supporting model-based reasoning and dynamic assessment of students’ reasoning. This is followed by an outline of a model for game-based dialog to support explanation generation and analysis. This explanation dialog model leverages CAT techniques and hidden Markov modeling to develop and refine an ongoing analysis of a students’ understanding within the game based on students’ explanations within the dialog and their other actions within the game.

Learning to Deflect: Conceptual Change in Physics During Digital Game Play

How does deep conceptual change occur when students play well-designed educational games? To answer this question, we present a case study in the form of a microgenetic analysis of a student’s processes of knowledge construction as he played a conceptually-integrated digital game (SURGE Next) designed to support learning about Newtonian mechanics. Grounded in the Knowledge In Pieces framework of conceptual change (A. diSessa, 1993), we analyze the processes through which the student, Jamal, developed an expert-like understanding of deflections, a phenomenon that has been previously identified as challenging to understand for novice physics learners. We also explore the key characteristics of SURGE Next supporting these conceptual change processes. Our analysis shows that Jamal’s learning involved iterative refinement of his conceptual understanding through distributed encoding (A. diSessa, 1993). That is, as Jamal advanced through the game levels in SURGE Next, he developed a progressively more distributed sense of mechanism (A. diSessa, 1993) and was able to identify and operationalize the roles of the direction and magnitude of an object’s initial (or previous) velocity in determining the velocity resulting from the application of a new impulse. We also discuss the methodological and design implications of our findings for future research on digital games for learning.

Digital Games as Multirepresentational Environments for Science Learning: Implications for Theory, Research, and Design

Environments in which learning involves coordinating multiple external representations (MERs) can productively support learners in making sense of complex models and relationships. Educational digital games provide an increasing popular medium for engaging students in manipulating and exploring such models and relationships. This article applies cognitive science research on MERs to a range of popular educational and recreational games that focus on the interpretation and manipulation of models. We leverage the literatures on embodied cognition, adaptive scaffolding, science education, and dynamic visualizations to address the challenges, trade-offs, and questions highlighted by the research. We apply these research-derived design considerations to analyze (a) the extent and forms through which the design considerations are reflected in the design of the games, (b) the implications for designing effective model-based games for learning, and (c) the implications for future research on MERs.