Abstract

Microlearning is a pedagogical strategy that separates materials into small units for learners to understand quickly, commonly presented in a digital learning environment with easy accessibility. This approach has gained increasing attention in higher education with its student-centred characteristics and technology integration capabilities. This article describes the creation of a microlearning course focused on referencing skills for English for Academic Purposes (EAP) modules as a supplementary learning resource. Two AI tools were utilized to facilitate the creation process: an AI course generator and an AI video generator. The article starts with background information and briefly discusses the microlearning strategy. It then details the course design and creation process. Finally, it concludes with a discussion of the course development and suggestions for potential microlearning projects.

Introduction

Background

Referencing is a crucial academic skill that university students must acquire; however, mastering the referencing skills can often be challenging for learners (Zhang, 2018). One of the issues is that some students might not recognize the importance of referencing skills, compared to other academic and research competencies, potentially leading to a lack of motivation to learn these skills (Zhang, 2018). Another is that teachers may face difficulties teaching referencing rules effectively due to the limited class time, and students may not be provided sufficient opportunities to comprehend and practice the complex rules. An online platform can help solve the problems, where students can develop referencing skills via interactive activities based on their availability outside the traditional classroom.

Microlearning

Microlearning has gained much attention in higher education with its student-centred approach and the ability to integrate with technology (Alias and Razak, 2023). According to Corbeil and Corbeil (2024), the rapid growth of social media platforms and mobile device users has accelerated microlearning in both work and educational environments. Learners, showing a shift in learning behaviour, prefer accessing information on single topics presented in short and focused units on mobile devices (Taylor and Hung, 2022). 

Microlearning is a teaching strategy that breaks complex knowledge into manageable units, typically not exceeding five minutes (Lee, Jahnke and Austin, 2021). Courses that adopt a microlearning approach are structured into small units, each focusing on a specific skill or concept that learners can comprehend with less effort (Yao and Ho, 2024). This strategy aligns with contemporary students' learning preferences for rapid learning (Corbeil and Corbeil, 2024). In addition, microlearning lessons are often delivered through web-based or mobile platforms (Taylor and Hung, 2022). Technologies employed in microlearning platforms include video-based mini-lectures, gamification elements and interactive quizzes. 

Research has shown the effectiveness of microlearning in improving students' task-based performances, such as successfully completing specific tasks or acquiring new knowledge (Taylor and Hung, 2022). Moreover, microlearning has enhanced learners' motivation, confidence and self-perception (Lee, Jahnke and Austin, 2021; Lee, 2023). This approach has also been particularly beneficial as a supplementary learning resource for large academic programs (Taylor and Hung, 2022). Despite its positive outcomes, current studies on microlearning remain limited and are focused on fields such as medicine or healthcare (Taylor and Hung, 2022). Hence, further research across diverse disciplines is necessary to fully understand the potential of microlearning. 

Microlearning reduces students' cognitive load by breaking complex knowledge into manageable units, enabling them to reinforce knowledge through repetition at their own pace (Oxford Learning, 2025). In addition, teachers can use a microlearning approach to design mini-units for complex subjects to scaffold students' learning processes. Thus, an online microlearning course focused on the Harvard referencing style was developed to help EAP students at XJTLU improve their referencing skills.

Course creation and design

This section will introduce two AI tools used in the course creation, then outline the course structure and describe the unit content design.

1.    AI tools

Two AI tools, MiniCourseGenerator and D-ID, were used to support the course creation. 

Mini-course generator 

MiniCourseGenerator (https://minicoursegenerator.com/) is an AI-powered platform utilizing a card-based structure to organize the micro units. An entire microlearning course can be automatically generated using the platform's embedded AI assistant, and the content can later be edited and adjusted to meet specific learning objectives. Learners can access the course via different devices, such as mobile phones, tablets or laptops. However, as the course was designed for in-house use and tailored to XJTLU's specific learning needs, the author created the course content rather than relying on the AI assistant. In addition, AI-generated content for the XJTLU Harvard referencing style was often inaccurate and lengthy, which did not align with the course learning objectives and microlearning approach. Thus, the author first created a draft of the course content, ensuring accuracy and conciseness, and then transferred it to the online platform. The platform was primarily used to present the course, and its AI assistant was used to generate images and interactive activities based on the self-designed unit content.

D-ID 

D-ID (https://www.d-id.com/) is a platform that can generate videos featuring AI avatars. Traditionally, human instructors deliver microlearning units. For this course, D-ID was used to create short instructional videos with an AI speaker to facilitate the creation. In addition, an interactive AI agent was developed using D_ID to provide real-time responses to support the course's Frequently Asked Questions (FAQ) sections.

2.    Course structure

The course content was designed according to the two core elements of the Harvard referencing style: in-text citations and a reference list. Considering the complexity of the Harvard referencing system for novice learners, the course focuses on the most commonly used sources in student assignments. The course has three main sections: Cover Page, Part One: In-text citations, and Part Two: The Reference List. 

Cover page

The cover page introduces the XJTLU Harvard referencing system and provides a brief user guide for navigating the online course via an AI video with a speaker (See Figure 1). It also offers tips for a more efficient and tailored learning experience. For example, students can use the menu to select the specific citation skill rather than progressing through the lessons one by one.

Figure 1: Cover Page

Part One: In-Text Citation

This section focuses on students' most commonly used citation rules for their assignments. Topics include citing two, three and multiple authors, using direct quotes and referencing secondary sources. Follow-up quizzes and practices are provided to reinforce learning.

Part Two: Reference List

This section covers the lessons on identifying and referencing four common types of sources: journal articles, book chapters, printed books, and website sources; each unit also includes examples and practice exercises.

3.    Design of the unit content

Developing In-house materials

To assist students using the XJTLU Harvard referencing guide, the author addressed knowledge gaps that could pose difficulties for students in material design. For example, an introduction to commonly used source types was included, as students often find it challenging to reference correctly due to their unfamiliarity with types of sources, such as conference papers. Furthermore, the referencing guide emphasizes the rules but lacks detailed explanations, which may be challenging for students to comprehend. For instance, students may learn about including a DOI for online journal articles according to the formatting guidelines, but may not understand its meaning. Thus, two FAQ sections were added to clarify terms that may confuse learners. 

Adopting a microlearning approach with AI technologies

The key components of the course content are as follows:

1)    Bite-sized learning units

Each unit is focused on a single learning objective, which students can manage. The content uses brief messages, hints, or examples to illustrate the targeted skill while maintaining clarity (See Figure 2). 

2)    AI-featured micro lecture videos

Unlike the traditional videos delivered by human lecturers, an AI video with an avatar explains the targeted skills that lasts about one to three minutes (See Figure 3).

3)    AI-generated interactive practice 

The author used the AI assistant of the MiniCourseGenerator platform to create interactive activities based on the learning content, such as quizzes, matching exercises, and drag-and-drop. These practice activities assess students' understanding and offer immediate feedback (See Figure 4). 

4)    AI-generated images

AI-generated images were used as visual aids to enhance the comprehension of the learning content.

5)    Practices based on authentic materials

Authentic materials are employed to enhance learning. For example, students practice identifying elements from the screenshots of library search results or the front page of articles. The idea is to prepare students to recognize different types of sources and locate the elements needed for proper referencing.

Figure 2 Part 1:In-Text Citation, Unit 1 The Basics

Figure 3  Part 1: In-Text Citation, Unit 1 The Basics (A micro-lecture video featuring an AI avatar on how to apply the basic format of in-text citation)

Figure 4 Part 1: In-Text Citation, Unit 1 The Basics An interactive practice generated by AI based on the content

Additional features 

•    Certification

Learners automatically receive a certificate through the platform when completing the course. This certificate motivates students and acknowledges their efforts in completing the course.

•    AI agent for FAQ 

FAQ sections address students' common queries when citing sources or compiling a reference list. Questions include "How do I identify the author's surname?" or "What is a Doi?" An AI agent was created to provide immediate responses on referencing issues as an alternative to the written instructions (See Figure 5).

Figure 5： An AI agent for FAQ

Discussion and Conclusion

This article has described the creation of a micro-learning course focusing on referencing skills with AI technology. The materials were designed to meet students' learning needs, and the content was delivered in digestible units to scaffold their learning process. The two AI tools, MiniCourseGenerator and the D-ID, facilitated and enhanced online course production and video creation. For example, AI-generated interactive quizzes can be created within minutes based on the learning unit, significantly reducing teachers' workload in designing activities. In addition, building an AI agent takes only a few simple steps without requiring users' technical skills.

The discussion regarding the development of the microlearning course will focus on three main aspects: topic selection, material development, and online learning motivation. First, as an educational strategy focusing on developing skills through concise units for rapid learning, microlearning can be effective for topics like mastering referencing skills, which can be learnt separately and require more practical practice and less theoretical knowledge. Microlearning may not be suitable for subjects requiring an in-depth understanding. For example, this course is primarily designed to train basic referencing skills that benefit from practice, such as applying referencing rules, instead of addressing more advanced competencies, such as identifying information types, integrating sources, or paraphrasing. 

Second, creating microlearning course materials can be as challenging as developing traditional course content. To reduce the workload, teachers can adapt the existing materials from their teaching subjects and focus on basic skills. For example, in writing courses, the course design could begin with basic ones such as brainstorming or identifying essay structure elements for pre- or post-learning activities. The content should be concise and manageable for students. However, microlearning might not be suitable for learners who prefer traditional teaching styles with extensive details and longer instructional formats.

Third, microlearning integrates technology to facilitate course production processes for teachers and provide learners easy access across various devices. However, the fixed and repetitive online units may decrease learner motivation and engagement over time. Teachers or schools may consider implementing micro-credentials to motivate students to participate in the course (Varadarajan, Koh, and Daniel, 2023). Future development of microlearning courses could advance the certificate of completion into assessment-based credentials to recognize students' accomplishment of skills (Clements, West and Hunsaker, 2020). 

The online course, utilizing a microlearning approach enhanced by AI tools, offers a new method to help students improve their referencing skills. Microlearning has shown its potential to facilitate skill acquisition by catering to learners' preferences for concise, focused and digital instructional materials. This approach is recommended for training basic skills rather than subjects requiring comprehensive and in-depth learning. Micro-credentials could be incorporated to recognize students' achievements and boost their engagement.

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