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

Math Learning Environment with Game-Like Elements and Causal Modeling of User Data

Educational games intend to make learning more enjoyable, but at the potential cost of compromising learning efficiency. Therefore, instead of creating educational games, we create learning environment with game-like elements: the elements of games that are engaging. Our approach is to assess each game-like element in terms of benefits such as enhancing engagement as well as its costs such as sensory or working memory overload, with a goal of maximizing both engagement and learning. We developed different four versions of a math tutor with different degree of being game-like such as adding narrative and visual feedback. Based on a study with 297 students, we found that students reported more satisfaction with more \u27game-like\u27 tutor but we were not able to detect any conclusive difference in learning among the different tutors. We collected student data of various types such as their attitude and enjoyment via surveys, performance within tutor via logging, and learning as measured by a pre/post-test. We created a causal model using software TETRAD and contrast the causal modeling approach to the results we achieve with traditional approaches such as correlation matrix and multiple regression. Relative to traditional approaches, we found that causal modeling did a better job at detecting and representing spurious association, and direct and indirect effects within variables. Causal model, augmented with domain knowledge about likely causal relationships, resulted in much more plausible and interpretable model. We propose a framework for blending exploratory results from causal modeling with randomized controlled studies to validate hypotheses

Chapter 1 : Learning Online

The OTiS (Online Teaching in Scotland) programme, run by the now defunct Scotcit programme, ran an International e-Workshop on Developing Online Tutoring Skills which was held between 8–12 May 2000. It was organised by Heriot–Watt University, Edinburgh and The Robert Gordon University, Aberdeen, UK. Out of this workshop came the seminal Online Tutoring E-Book, a generic primer on e-learning pedagogy and methodology, full of practical implementation guidelines. Although the Scotcit programme ended some years ago, the E-Book has been copied to the SONET site as a series of PDF files, which are now available via the ALT Open Access Repository. The editor, Carol Higgison, is currently working in e-learning at the University of Bradford (see her staff profile) and is the Chair of the Association for Learning Technology (ALT)

Reciprocal peer tutoring and treatment integrity of elementary school students

Academic concerns are the most common reason students are referred for special services in schools. This obviously leads to the necessity for schools to have secondary prevention services in place to address the needs of students who are struggling. Peer tutoring, in its various forms, has been well documented as an effective and inexpensive intervention for all academic areas. Despite the promise of peer tutoring, research evidence suggests that teachers may not consistently carry out their roles in the peer tutoring process with sufficient accuracy to ensure positive outcomes. One possible solution to this problem is to have a consultant directly monitor the intervention. The purpose of this study was to use the well established procedures of Reciprocal Peer Tutoring and Classwide Peer Tutoring to develop an effective peer tutoring process that can be implemented with an absolute minimum of teacher involvement. Students were responsible for initiating the tutoring sessions, collecting data, evaluating their performances, and administering rewards. Students\u27 work was evaluated and monitored by the consultant rather than the teacher. The results demonstrated that the students implemented the reciprocal peer tutoring procedures with high accuracy and integrity. As a result, the students showed increases in their sight word acquisition. Limitations and future directions are discussed

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

A Causal-Comparative Study on the Efficacy of Intelligent Tutoring Systems on Middle-Grade Math Achievement

This study is a quantitative examination of intelligent tutoring systems in two similar suburban middle schools (grades 6-8) in the Southeastern United States. More specifically, it is a causal-comparative study purposed with examining the efficacy of intelligent tutoring systems as they relate to math achievement for students at two similar middle schools in the Midlands of South Carolina. The independent variable, use of an intelligent tutoring system in math instruction, is defined as the supplementary use of two intelligent tutoring systems, Pearson’s Math Digits and IXL, for math instruction. The dependent variable is math achievement as determined by the Measures of Academic Progress (MAP) SC 6+Math test. The student data examined is archived MAP SC 6+ Math scores from the 2017-2018 school year. A one-way ANCOVA was used to compare the mean achievement gain scores of both groups, students whose math instruction included intelligent tutoring systems and students whose math instruction did not include intelligent tutoring systems, to establish whether or not there was any statistically significant difference between the adjusted population means of the two independent groups. The results showed that the adjusted mean of posttest scores of students who did not receive math instruction that involved an intelligent tutoring system were significantly higher than those who did

Digital Transformation of Additional Professional Education: Features of the LK-14 Educational Platform

This article substantiates the relevance of the transformation of the educational environment of additional professional education (APE) in the Republic of Sakha (Yakutia). This study aims to justify the transformation of the educational environment of APE in the context of digitalization and to consider the prospects for targeted professional development of teachers in the republic according to their needs. The authors chose this scientific topic due to the pressing needs of Russian continuing professional education (CPE) and current problems such as the lack of unified approaches and mechanisms for regulating the professional development of teachers in the digital educational environment and the lack of methods for monitoring the effectiveness and efficiency of CPE distance learning programs. Creating an innovative and dynamic CPE system requires the intensive introduction of information technologies into education. These technologies ensure that the learning process is open and of high quality, as well as provide access to global educational resources. This helps learners create “their own individual educational environment” reflecting their needs and requirements. The research methods used to explore this problem were a pedagogical experiment, the analysis of the organization of CPE of teachers in the region, designing a regional model of targeted personalized training of educators and administration. The research results include the specifics of APE modernization in the region and the model of targeted personalized training of teachers of the republic. The qualitative novelty of this model stems from the fact that developing teachers’ competencies involves identifying gaps in their professional knowledge and building individual learning paths