Motivational Theories in Action: A Guide for Teaching Artificial Intelligence Prompts to Support Student Learning Motivation

Abstract

This conceptual study explores how motivational theories can guide the use of generative Artificial Intelligence (AI) tools, such as ChatGPT, to enhance student learning motivation. Drawing on Self-Determination Theory (SDT), Expectancy-Value Theory (EVT), and Mindset Theory (MT), we introduce the Motivation Construction Model (MCM), a theoretical framework consisting of three interrelated phases: contemplation, goal setting & planning, and action. We demonstrate how MCM can be applied in AI-driven learning environments to support personalized prompts, targeted feedback, and adaptive guidance to motivate learning. We propose that MCM is a strategic and holistic approach to equip educators with actionable guidelines to use AI for motivating students while adhering to ethical pedagogical principles. Although the MCM framework is grounded in established motivational theories, its real-world application remains to be explored. Future research should examine the effectiveness of MCM in authentic classroom contexts to better understand its potential for enhancing student motivation and informing evidence-based instructional practices.