Interaction patterns in exploratory learning environments for mathematics: a sequential analysis of feedback and external representations in Chinese schools

Feedback in exploratory learning systems has been depicted as an important contributor to encourage exploration. However, few studies have explored learners’ interaction patterns associated with feedback and the use of external representations in exploratory learning environments. This study used Fractions Lab, an exploratory learning environment for mathematics, to facilitate children’s conceptual understanding of fractions in three Chinese schools. Students (n = 189) from six different classes were invited to use Fractions Lab, and 260,000 event logs were collected. Beyond demonstrating the overall efficacy of the approach, lag sequential analysis supported us in approaching a deeper understanding of patterns of interaction. The findings highlight that the design of three-levels of feedback (Socratic, guidance, and didactic-procedural feedback) played different roles in supporting students to use external representations to perform mathematical tasks in an exploratory learning environment. This study sheds light on how these interaction patterns might be applied to the Fractions Lab system in order to provide increasingly tailored support, based on cultural differences, to enhance students’ technology-mediated learning experiences

인공지능 기반 교육 플랫폼 사용에 대한 중국 교사의 인식

학위논문 (석사) -- 서울대학교 대학원 : 사범대학 교육학과, 2021. 2. 조영환.최근 교육 분야에서 인공지능(AI)의 도입이 큰 관심을 끌고 있다. 특히 AI 기술과 학습 분석이 결합한 인공지능 기반 교육 플랫폼은 지금껏 실현되기 어려웠던 맞춤형 학습(personalized learning)과 적응적 학습(adaptive learning)에 도움이 될 수 있도록 발전하고 있다. 인공지능 기반 교육 플랫폼(AI-based education platform)은 학습자의 행동 추적 등을 통해 이들의 특성을 분석하고 진단을 제공한 뒤 분석 결과를 토대로 학습자에게 인지 수준에 맞는 맞춤형 학습자원과 피드백을 제공한다. 인공지능 기반 교육 플랫폼은 교사와 학생에게 실시간 학습 데이터와 분석 결과, 그리고 피드백을 제공할 수 있어 인공지능 기반 교육 플랫폼이 맞춤형 학습에 긍정적인 의미가 있다는 선행 연구도 있었다. 그럼에도 불구하고, 기존 연구는 모델 개발의 차원에서나 엄밀한 실험실 환경에서 인공지능 기반 교육 플랫폼의 효과를 연구해왔으며, 인공지능 기반 교육 플랫폼에 대한 교사의 인식과 관련된 연구는 드물었다. 교사는 인공지능 교육 기술의 사용자이기 때문에 인공지능 교육 기술의 교육 도입에 있어 교사들의 인식과 의견은 중요하다. 본 연구는 인공지능 기반 교육 플랫폼을 활용하는 것에 대한 교사들의 인식을 탐구하였다. 아래 연구 문제를 다루기 위해 질적 연구를 시행하였다. 첫째, 중국 교사들은 인공지능 기반 교육 플랫폼이 중학교 교육에 활용 있어 어떠한 장점이 있다고 인식하는가? 둘째, 중국 교사들은 인공지능 기반 교육 플랫폼과 중학교 교수 활동 요소 간 어떠한 모순이 있다고 인식하는가? 셋째, 중국 교사들은 인공지능 기반 교육 플랫폼을 중학교 교육에 도입할 때 무엇이 필요하다고 인식하는가? 본 연구는 중국 교사들을 연구대상으로 온라인 심층 면담을 하였다. 문헌 리뷰를 통해 면담 질문지를 설계하되 눈덩이표집법 (snowball sampling)을 통해 중국 중학교 교사 14명을 연구참여자로 선정하였다. 선정된 교사들은 모두 인공지능 기반 교육 플랫폼 사용 경험이 있으며 각 교사를 대상으로 약 1시간 정도 면담을 진행하고 녹음하였다. 면담이 끝난 후 녹음 내용을 전사하였으며, 주제분석을 사용하여 면담 내용을 초기 코드 생성하고 면담 자료 속에서 주제를 도출하였다. 특히 연구 문제 2번의 경우, 인공지능 기반 교육 플랫폼 활용과 교수 학습활동 내 여러 요소 간의 모순을 분석하기 위해 활동이론을 연구의 틀로 이용하였다. 최종적으로 연구문제 1에 대한 주제 4개, 연구문제 2에 대한 주제 6개, 연구문제 3에 대한 주제 4개를 도출하였다. 연구 결과로 교사들은 인공지능 기반 교육 플랫폼의 장점에 대해 즉각적인 피드백 제공, 교수학습 지원, 교사의 업무량 감소 등으로 인식하였고, 인공지능 기반 교육 플랫폼이 다양한 교수학습 자원을 통합할 수 있다고 인식하였다. 아울러 교사들은 인공지능 기반 교육 플랫폼의 사용에 있어 기존의 교수학습 활동과 상충된 부분이 있다는 점을 인식하였다. 교사들은 기존 인공지능 기반 교육 플랫폼의 추천 모델이 차별화된 학생들에게 잘 적용되지 못한다는 것을 인식하였다. 그리고 기존 인공지능 기반 교육 플랫폼이 다양한 학습 자원을 잘 분류되지 못하기 때문에 교사들이 사용하기 불편하다. 인공지능 기반 교육 플랫폼을 이용할 때 교사의 지적재산권을 보호하기 위한 명확한 규제가 부족하다고 인식하였다. 이와 함께 학부모들은 인공지능 기반 교육 플랫폼을 사용함으로써 발생할 수 있는 학습자의 인터넷 남용과 시력 저하 문제를 우려하였다. 또 중국의 사회문화적 배경과 교육 특성으로 인해 인공지능 기반 교육 플랫폼을 활용하는 데 학생들의 글씨 쓰기 능력에 영향을 미칠 수 있으며, 학교 내 전자기기 사용 제한도 데이터 수집의 지속성과 효율성에 영향을 미칠 수 있다고 인식하였다. 교사들은 위의 문제들이 인공지능 교육 플랫폼 사용에 대한 규칙 마련과 인공지능 기술을 개선함으로써 완화될 수 있다고 인식하였다. 또한 교사의 실제 요구에 맞게 개발될 수 있도록 인공지능 기반 교육 플랫폼 개발 과정에 교육 전문가와 교사가 참여할 필요가 있다. 본 연구는 중국 교사들이 인공지능 기반 교육 플랫폼에 대한 인식을 탐색하였으며, 인공지능 기반 교육 플랫폼이 교수학습에서의 장점과 문제점을 밝혔다. 아울러 본 연구는 인공지능 기반 교육 플랫폼이 교육 분야에 대규모로 도입될 수 있도록 규칙, 인공지능 기술, 그리고 교육 공학의 차원에서 사용 규범과 기술 개선을 제안하였다. 본 연구를 통해 탐색한 내용이 향후 교육 분야의 인공지능 기반 교육 플랫폼 도입에 활용된다면 인공지능 교육 기술에 관한 연구의 발전에도 기여할 수 있을 것으로 기대된다.In recent years, the introduction of artificial intelligence (AI) in education has attracted widespread attention. In particular, the AI-based education platform based on the combination of AI technology and learning analysis brings new light to the long-standing difficulties in personalized learning and adaptive learning. The AI-based education platform analyzes learners' characteristics by collecting their data and tracking their learning behavior. It then generates cognitive diagnosis for learners and provides them with personalized learning resources and adaptive feedback that match their cognitive level based on systematic analysis. With the help of the AI-based education platform, teachers and students can get real-time educational data and analysis result，as well as the feedback and treatment corresponding to the results. Previous studies have already demonstrated and proved its positive significance to personalized learning. However, these studies mostly start from a model development perspective or in a rigorous laboratory environment. There has been little research on teachers' perceptions of AI-based education platform. As a direct user of AI educational technologies, teachers' perceptions and suggestions are vital for introducing AIEd in education. In this study, the researcher explored teachers' perceptions of using AI-based education platform in teaching. The study conducted qualitative research to address the following research questions: 1) How do Chinese teachers perceive the advantages of AI-based education platforms for teaching and learning in secondary school? 2) How do Chinese teachers perceive the contradictions between AI-based education platforms and the secondary school system? 3）How do Chinese teachers suggest applying AI-based education platforms in secondary school? And it referred to the in-depth online interview with Chinese teachers who had experience with AI-based education platform. Interview questions were constructed through the literature review, and 14 secondary school teachers were selected by the snowball sampling method. The interviews lasted for an average of one hour per teacher and were transcribed from the audio recordings to text documents when finished. Afterward, the data were analyzed using thematic analysis, including generating initial codes, searching and reviewing the categories, and deriving the themes finally. Notably, for research question two, the researcher used the activity theory framework to analyze the contradictions among the use of the AI-based education platform and the various elements of the teaching and learning activities. Finally, four themes for research question 1, six themes for research question 2, and four themes for research question 3 were derived. As for the advantages, teachers believe that AI-based education platforms can provide instant feedback, targeted and systematic teaching support, and reduce teachers' workload. At the same time, AI-based education platforms can also integrate teaching resources in different areas. Teachers also recognized that the AI-based education platforms might trigger contradictions in existing teaching activities. They are aware of the situation that the recommended model of the AI-based education platform is not suitable for all levels of students; that a large number of learning resources are not classified properly enough to meet the needs of teachers, and that there lack clear rules and regulations to protect teachers' intellectual property rights when using the platform. Besides, parents are also concerned about the potential risk of internet addiction and vision problems using AI-based education platforms. Moreover, the use of the AI-based education platform may also affect students' ability to write Chinese characters due to the socio-historical background and educational characteristics in China. Furthermore, the restricted use of electronic devices on campus may also impact the consistent and effective education data collection. Teachers believe that these problems can be solved by improving rules and AI technology. Moreover, to make the platform more in line with the actual teaching requirements, teachers and education experts can also be involved in the development process of AI-based education platform. This study explored how Chinese teachers perceive the AI-based education platform and found that the AI-based education platform was conducive to personalized teaching and learning. At the same time, this study put forward some suggestions from the perspective of rules, AI technology, and educational technology, hoping to provide a good value for the future large-scale introduction of AI-based education platforms in education.CHAPTER 1. INTRODUCTION 1 1.1. Problem Statement 1 1.2. Purpose of Research 7 1.3. Definition of Terms 8 CHAPTER 2. LITERATURE REVIEW 10 2.1. AI in Education 10 2.1.1 AI for Learning and Teaching 10 2.1.2 AI-based Education Platform 14 2.1.3 Teachers' Perception on AI-based Education Platform 18 2.2. Activity Theory 20 CHAPTER 3. RESEARCH METHOD 23 3.1. Research Design 23 3.2. Participants 25 3.3. Instrumentation 26 3.3.1 Potential Value of AI System in Education 26 3.4. Data Collection 33 3.5. Data Analysis 34 CHAPTER 4. FINDINGS 36 4.1. Advantages of Using AI-based Education Platform 36 4.1.1 Instant Feedback 37 4.1.2 Targeted and Systematic Teaching Support 42 4.1.3 Educational Resources Sharing 46 4.1.4 Reducing Workload 49 4.2. Tensions of Using AI-based Education Platform 51 4.2.1 Inadequately Meet the Needs of Teachers 52 4.2.2 Failure to Satisfy Low and High Achievers 54 4.2.3 Intellectual Property Violation 56 4.2.4 Guardian's Concern 57 4.2.5 School Rules about the Use of Electronic Devices 58 4.2.6 Implication for Chinese Character Education 59 4.3. Suggestion of Using AI-based Education Platform 61 4.3.1 Improving Rules of Using the AI-based Education Platform 61 4.3.2 Improving Rules of Protecting Teachers Right 62 4.3.3 Improving AI Technology 64 4.3.4 Participatory Design 66 CHAPTER 5. DISCUSSION AND CONCLUSION 68 5.1. Discussion 68 5.2. Conclusion 72 REFERENCE 75 APPENDIX 1 98 APPENDIX 2 100 국문초록 112Maste

State of the art and practice in AI in education

Recent developments in Artificial Intelligence (AI) have generated great expectations for the future impact of AI in education and learning (AIED). Often these expectations have been based on misunderstanding current technical possibilities, lack of knowledge about state-of-the-art AI in education, and exceedingly narrow views on the functions of education in society. In this article, we provide a review of existing AI systems in education and their pedagogic and educational assumptions. We develop a typology of AIED systems and describe different ways of using AI in education and learning, show how these are grounded in different interpretations of what AI and education is or could be, and discuss some potential roadblocks on the AIED highway

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Personalized education, tailored to individual student needs, leverages educational technology and artificial intelligence (AI) in the digital age to enhance learning effectiveness. The integration of AI in educational platforms provides insights into academic performance, learning preferences, and behaviors, optimizing the personal learning process. Driven by data mining techniques, it not only benefits students but also provides educators and institutions with tools to craft customized learning experiences. To offer a comprehensive review of recent advancements in personalized educational data mining, this paper focuses on four primary scenarios: educational recommendation, cognitive diagnosis, knowledge tracing, and learning analysis. This paper presents a structured taxonomy for each area, compiles commonly used datasets, and identifies future research directions, emphasizing the role of data mining in enhancing personalized education and paving the way for future exploration and innovation.Comment: 25 pages, 5 figure

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Systematic review of research on artificial intelligence applications in higher education – where are the educators?

According to various international reports, Artificial Intelligence in Education (AIEd) is one of the currently emerging fields in educational technology. Whilst it has been around for about 30 years, it is still unclear for educators how to make pedagogical advantage of it on a broader scale, and how it can actually impact meaningfully on teaching and learning in higher education. This paper seeks to provide an overview of research on AI applications in higher education through a systematic review. Out of 2656 initially identified publications for the period between 2007 and 2018, 146 articles were included for final synthesis, according to explicit inclusion and exclusion criteria. The descriptive results show that most of the disciplines involved in AIEd papers come from Computer Science and STEM, and that quantitative methods were the most frequently used in empirical studies. The synthesis of results presents four areas of AIEd applications in academic support services, and institutional and administrative services: 1. profiling and prediction, 2. assessment and evaluation, 3. adaptive systems and personalisation, and 4. intelligent tutoring systems. The conclusions reflect on the almost lack of critical reflection of challenges and risks of AIEd, the weak connection to theoretical pedagogical perspectives, and the need for further exploration of ethical and educational approaches in the application of AIEd in higher education

AI in Learning: Designing the Future

AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This open access book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning. This book will be of use to a variety of readers, including researchers, AI users, companies and policy makers