Programming and Computational Thinking in Mathematics Education

Tamborg, Andreas Lindenskov; Elicer, Raimundo

doi:10.1007/s13218-021-00753-3

Cited by 11 publications

(1 citation statement)

References 28 publications

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“…Such processes (Exploring and Expressing) were evident in other, more recent, projects. For example, the ScratchMaths project that explored students' mathematics learning during structured interactions with the Scratch programming language (e.g., [32]), which also considered CT's influence towards mathematical learning (as suggested in [7]). This project offered a framework of design principles for the actions learners get to use when programming.…”

Section: Digital Technology As a Gateway To Overcome Difficulties Wit...mentioning

confidence: 99%

How Learning to Speak the Language of a Computer-Based Digital Environment Can Plant Seeds of Algebraic Generalisation: The Case of a 12-Year-Old Student and eXpresser

Baccaglini-Frank,

Geraniou,

Hoyles

et al. 2024

Education Sciences

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When learning in a digital interactive mathematics learning environment (DIMLE) designed to foster the development of specific mathematics content, students come to express their ideas through different languages and representations. We devise a method based on the Theory of Instrumental Genesis (TIG) to analyse aspects of a middle school student’s learning about algebraic generalisation in a DIMLE called “eXpresser”. Our analytic scheme allows us to capture changes in her instrumented schemes when accomplishing a certain task repeatedly, gradually modifying her interactions with the system. The results concern both insights into a specific mathematics learning journey in a DIMLE, and methodological progress at a more general level. Indeed, the method we devised and explored in this specific case can be applied to infer students’ schemes from their actions as they interact with other DIMLEs. This possibility yields great potential because more and more actions can now be recognized directly by software. This has important implications for computer-supported personalised learning, and AI in general.

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Section: Digital Technology As a Gateway To Overcome Difficulties Wit...mentioning

confidence: 99%

How Learning to Speak the Language of a Computer-Based Digital Environment Can Plant Seeds of Algebraic Generalisation: The Case of a 12-Year-Old Student and eXpresser

Baccaglini-Frank,

Geraniou,

Hoyles

et al. 2024

Education Sciences

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AI Literacy Education in Secondary Schools

Leung

et al. 2022

AI Literacy in K-16 Classrooms

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A Retrospective Analysis of Artificial Intelligence in Education (AIEd) Studies: Perspectives, Learning Theories, Challenges, and Emerging Opportunities

Mohammed,

Velander,

Milrad

2024

Lecture Notes in Educational Technology

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Recent advances in Information and Communication Technologies (ICT), especially AI-powered tools, are driving innovation and productivity across academic and industrial sectors. These technologies are also transforming education by enabling personalized learning, redefining teaching methods, and enhancing educational outcomes. Given the transformative potential of Artificial Intelligence in Education (AIEd), it is essential to examine its benefits and implications for the future of education. AI tools offer substantial benefits to various educational stakeholders by enhancing cognitive engagement, improving teaching assessments, and fostering digital literacy. Additionally, they support policy development, address ethical considerations, and increase educational efficiency and accessibility. However, despite AI’s potential in education, the rapid pace of technological change can create uncertainty and overwhelm, even among experts. As AIEd advances, it is crucial to develop strategies that help educators and institutions stay updated on new developments and integrate them effectively into educational settings. This study explores the historical development of AIEd and identifies current research trends through a dual-method approach. First, a bibliometric analysis using VOSViewer uncovers patterns in AIEd research over the past 50 years. Second, text mining techniques using term frequency analysis and topic modeling—examine over 2,204 abstracts from Scopus, covering publications from 1970 to the present. By combining these methods, the study highlights key AIEd research areas that impact stakeholders and influence future educational practices. Understanding the evolution of AIEd and current trends is essential for anticipating its future trajectory, preparing us to address emerging challenges and opportunities in education. The findings trace the progression of AIEd research, revealing shifts in focus, underlying learning theories, and application paradigms. This comprehensive overview helps identify research gaps and emerging themes, supporting the development of strategies to leverage AIEd’s potential in transforming education and meeting the complex, evolving needs of twenty-first century stakeholders.

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Programming and Computational Thinking in Mathematics Education

Cited by 11 publications

References 28 publications

How Learning to Speak the Language of a Computer-Based Digital Environment Can Plant Seeds of Algebraic Generalisation: The Case of a 12-Year-Old Student and eXpresser

How Learning to Speak the Language of a Computer-Based Digital Environment Can Plant Seeds of Algebraic Generalisation: The Case of a 12-Year-Old Student and eXpresser

AI Literacy Education in Secondary Schools

A Retrospective Analysis of Artificial Intelligence in Education (AIEd) Studies: Perspectives, Learning Theories, Challenges, and Emerging Opportunities

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