Presentation Information
[SS-8-01]Development of an Online Tandem Learning Support System to Promote Motivation: A Psychological Approach and Practical Application of Generative AI
*Atsushi Matsuki1 (1. Rikkyo University)
Keywords:
Online Tandem Learning,Self-Regulated Learning,Generative AI,Motivational Design,Learning Support System,Virtual Exchange
受講者に求められる 事前の知識・経験等
プログラミング知識やシステム開発の経験は一切不要です。また、心理学的な用語もできる限り平易な表現で説明いたしますので、心理学の専門知識も不要です。
オンライン学習のモチベーション維持や学習の質保証を目的として、心理学的なアプローチを用いて非エンジニアが生成AIで作成したシステムを共有します。このシステム開発の経験を通して生成AIによる学習システム開発の展望について説明します。また、実際、どの様な手順でシステムを構築したのかデモンストレーションを行い、現場で活用できるようなセッションといたします。
特に以下に該当する方の参加をお待ちしております。
（１）生成AIを用いて業務用のアプリケーション構築をしたい方
（２）オンラインタンデム学習に関心をお持ちの方
（３）オンライン学習のモチベーション維持に興味のある方
（４）教育システム構築に関心のある方
（５）規模の小さいプログラムのため予算を確保できないとお悩みの方
（６）プログラムに取り組むことで業務負荷が増すため、プログラム導入を躊躇されている方
＜注意点＞
＊今回説明するシステム構築は、主にGoogle for Workspaceでの実践となりますが、それ以外の方にも参考となる内容です。
＊高度なシステム構築のセッションではないため、すでに生成AIを用いてシステム構築の実践が多数ある方には、システム構築のデモンストレーションは不向きですのでご注意ください。
受講者が受講前に取り組む 事前課題等
当日、身近な課題で解決したい問題についてアンケートを取ります。回答の中から、その場で速やかに対応できそうな課題があれば、デモンストレーションの時間で、生成AIによるウェブアプリケーションを作成を実践いたしますので、身近な課題をお持ち寄りください
概要
1. Introduction
This presentation reports on the implementation and future prospects of an online tandem learning support system developed using generative AI, grounded in psychological insights to maintain and promote learner motivation. The presenter, a non-engineer, will share practical insights into translating psychological theories into system requirements, including the actual prompt engineering process. This initiative is part of the "ACE eTandem Program" under the ACE Consortium, supported by MEXT’s "Inter-University Exchange Project."Following the launch of a pilot program with Seoul National University in October 2025, we focused on the critical roles of learner motivation and self-regulated learning in ensuring the sustainability of online education (Muljana & Luo, 2019).
2. Overview of the Online Learning Record Notebook
Within the self-regulated learning cycle, evaluating achievements and challenges through self-reflection is known to enhance learner autonomy and sustained motivation (Zimmerman, 2002). Adopting a psychological approach, we developed an AI-powered "Online Learning Record Notebook" (the "Notebook") featuring the following functions to support continuous learning:
Mutual Support Function: Enables partners to view and provide feedback on each other's records, aiming to sustain motivation by satisfying the need for relatedness through reciprocity.
Self-Growth Function: Visualizes progress by allocating activity points to specific skills, thereby stimulating a sense of competence and enhancing learning engagement.
AI Suggestion Function: Reduces the psychological burden of topic depletion by allowing learners to consult the AI for conversation starters.
3. Results and Cost Evaluation
During the four-month pilot phase (N=4; 2 pairs), each pair completed over 10 sessions. While initial tracking via spreadsheets resulted in stagnant usage, the introduction of the Notebook significantly improved engagement. Post-program surveys revealed unanimous positive evaluations of the Notebook, with participants noting that providing feedback to their partners served as a key motivator. Notably, utilizing generative AI reduced the estimated four-month, four-million-yen outsourcing cost to approximately two months of in-house development, with ongoing expenses limited to AI API fees (approx. 2,500 JPY/month), demonstrating exceptional cost-effectiveness.
4. Future Prospects
To address the structural challenge where an increase in participants directly inflates administrative burdens, we are developing a matching application and automated orientation videos using generative AI. Restricting access to partner university students will ensure participant quality and reduce management overhead. We envision a streamlined ecosystem where distributing a single URL through partner institutions facilitates the entire process—from matching and orientation to Notebook recording and post-program surveys—culminating in the automated issuance of digital badges based on learning records.
5. Presentation Format and Interaction with Participants
This presentation will feature demonstrations of the developed systems and a mini-workshop where participants will collaboratively brainstorm AI prompts. Through substantive dialogue with practitioners from other institutions, we aim to provide a practical, hands-on session that yields actionable insights for their respective educational contexts.
プログラミング知識やシステム開発の経験は一切不要です。また、心理学的な用語もできる限り平易な表現で説明いたしますので、心理学の専門知識も不要です。
オンライン学習のモチベーション維持や学習の質保証を目的として、心理学的なアプローチを用いて非エンジニアが生成AIで作成したシステムを共有します。このシステム開発の経験を通して生成AIによる学習システム開発の展望について説明します。また、実際、どの様な手順でシステムを構築したのかデモンストレーションを行い、現場で活用できるようなセッションといたします。
特に以下に該当する方の参加をお待ちしております。
（１）生成AIを用いて業務用のアプリケーション構築をしたい方
（２）オンラインタンデム学習に関心をお持ちの方
（３）オンライン学習のモチベーション維持に興味のある方
（４）教育システム構築に関心のある方
（５）規模の小さいプログラムのため予算を確保できないとお悩みの方
（６）プログラムに取り組むことで業務負荷が増すため、プログラム導入を躊躇されている方
＜注意点＞
＊今回説明するシステム構築は、主にGoogle for Workspaceでの実践となりますが、それ以外の方にも参考となる内容です。
＊高度なシステム構築のセッションではないため、すでに生成AIを用いてシステム構築の実践が多数ある方には、システム構築のデモンストレーションは不向きですのでご注意ください。
受講者が受講前に取り組む 事前課題等
当日、身近な課題で解決したい問題についてアンケートを取ります。回答の中から、その場で速やかに対応できそうな課題があれば、デモンストレーションの時間で、生成AIによるウェブアプリケーションを作成を実践いたしますので、身近な課題をお持ち寄りください
概要
1. Introduction
This presentation reports on the implementation and future prospects of an online tandem learning support system developed using generative AI, grounded in psychological insights to maintain and promote learner motivation. The presenter, a non-engineer, will share practical insights into translating psychological theories into system requirements, including the actual prompt engineering process. This initiative is part of the "ACE eTandem Program" under the ACE Consortium, supported by MEXT’s "Inter-University Exchange Project."Following the launch of a pilot program with Seoul National University in October 2025, we focused on the critical roles of learner motivation and self-regulated learning in ensuring the sustainability of online education (Muljana & Luo, 2019).
2. Overview of the Online Learning Record Notebook
Within the self-regulated learning cycle, evaluating achievements and challenges through self-reflection is known to enhance learner autonomy and sustained motivation (Zimmerman, 2002). Adopting a psychological approach, we developed an AI-powered "Online Learning Record Notebook" (the "Notebook") featuring the following functions to support continuous learning:
Mutual Support Function: Enables partners to view and provide feedback on each other's records, aiming to sustain motivation by satisfying the need for relatedness through reciprocity.
Self-Growth Function: Visualizes progress by allocating activity points to specific skills, thereby stimulating a sense of competence and enhancing learning engagement.
AI Suggestion Function: Reduces the psychological burden of topic depletion by allowing learners to consult the AI for conversation starters.
3. Results and Cost Evaluation
During the four-month pilot phase (N=4; 2 pairs), each pair completed over 10 sessions. While initial tracking via spreadsheets resulted in stagnant usage, the introduction of the Notebook significantly improved engagement. Post-program surveys revealed unanimous positive evaluations of the Notebook, with participants noting that providing feedback to their partners served as a key motivator. Notably, utilizing generative AI reduced the estimated four-month, four-million-yen outsourcing cost to approximately two months of in-house development, with ongoing expenses limited to AI API fees (approx. 2,500 JPY/month), demonstrating exceptional cost-effectiveness.
4. Future Prospects
To address the structural challenge where an increase in participants directly inflates administrative burdens, we are developing a matching application and automated orientation videos using generative AI. Restricting access to partner university students will ensure participant quality and reduce management overhead. We envision a streamlined ecosystem where distributing a single URL through partner institutions facilitates the entire process—from matching and orientation to Notebook recording and post-program surveys—culminating in the automated issuance of digital badges based on learning records.
5. Presentation Format and Interaction with Participants
This presentation will feature demonstrations of the developed systems and a mini-workshop where participants will collaboratively brainstorm AI prompts. Through substantive dialogue with practitioners from other institutions, we aim to provide a practical, hands-on session that yields actionable insights for their respective educational contexts.