探索语音机器人对加纳大学生多媒体编程教育的影响

IF 6.7 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Harry Barton Essel, Dimitrios Vlachopoulos, Henry Nunoo‐Mensah, John Opuni Amankwa
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Data were collected using an academic achievement test and semi‐structured interviews, which allowed for a more in‐depth analysis of the students' experiences with the VoiceBot. The results showed that how the VoiceBot was applied positively influenced student learning in the experimental cohort. Moreover, the focus group data demonstrated that the VoiceBot can be a valuable assistant for students and could be easily replicated in other courses. To the best of our knowledge, this study was the first to use VoiceBot to engage undergraduate students in Ghana, thus contributing to the growing literature stream on the development of VoiceBots to improve student learning experiences. 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引用次数: 0

摘要

对话式用户界面(CUI),包括允许用户通过语音与计算机对话的语音界面,正在受到广泛欢迎。语音机器人可以让用户实时收到回复,而不受通信设备的限制。语音机器人已在客户服务等领域进行了探索,以实现重复性查询的自动化,并帮助减少冗余任务;然而,它们尚未广泛应用于课堂。本研究旨在探索语音机器人的实施对学生学习的影响。研究采用了前测-后测设计,65 名参与研究的多媒体编程本科生被随机分配到代表 2 × 2 设计(实验组和对照组)的情景中。数据收集采用了学业成绩测试和半结构式访谈,以便更深入地分析学生使用 VoiceBot 的体验。结果显示,如何应用 VoiceBot 对实验组学生的学习产生了积极影响。此外,焦点小组的数据还表明,语音机器人对学生来说是一个有价值的助手,很容易在其他课程中推广。据我们所知,这项研究是加纳第一项使用语音机器人吸引本科生参与的研究,从而为越来越多的关于开发语音机器人以改善学生学习体验的文献流做出了贡献。本研究阐明了使用零编码技术的设计过程,该技术被认为是适合资源有限的教育机构的一种方法。 实践者注释关于本主题的已知内容 对话式用户界面(CUI),包括语音界面,已经得到普及,并被用于通过自然语言与计算机进行交互。语音机器人已被用于客户服务等多个领域,以实现任务自动化并减少冗余。WhatsApp 和 Telegram 等即时通讯系统已被用于教育领域的通信。人工智能(AI)和自然语言处理(NLP)技术的进步极大地改善了支持语音的 CUI(语音机器人)。现有研究表明,聊天机器人会影响学生的学习动机、学习体验和学习成绩;然而,利用语音机器人提高学习效率的研究还很有限。本文新增内容 在多媒体编程课程中引入语音机器人作为辅助工具,以促进学习。研究采用了实验设计,实验组使用配备了零编码 VoiceBot 的 WhatsApp 群组平台,对照组则没有配备 VoiceBot。研究发现,与 VoiceBot 互动的学生的学习成绩优于对照组。研究还就如何将语音机器人融入教育机构提出了明确的建议。对实践和/或政策的启示 研究结果表明,语音机器人可以在提高学生学习成绩方面发挥重要作用,尤其是在多媒体编程等科目上。教育机构可以建立由学科专家组成的学习设计和技术中心,将 VoiceBots 有效地融入学习过程。教师必须具备足够的技术能力,才能让学生使用语音机器人,因此有必要开展有针对性的在职培训。未来的研究可以探索语音机器人在不同学科领域和教育水平中的使用情况,分析使用模式对学习成果的影响,并评估其对学生参与和学习动机的长期影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the impact of VoiceBots on multimedia programming education among Ghanaian university students
Conversational user interfaces (CUI), including voice interfaces, which allow users to converse with computers via voice, are gaining wide popularity. VoiceBots allow users to receive a response in real‐time, regardless of the communication device. VoiceBots have been explored in fields such as customer service to automate repetitive queries and help reduce redundant tasks; however, they have not been widely applied in the classroom. This study aimed to explore the effects of VoiceBot implementation on student learning. A pre‐test–post‐test design was implemented with 65 participating undergraduate students in multimedia programming who were randomly allocated to scenarios representing a 2 × 2 design (experimental and control cohorts). Data were collected using an academic achievement test and semi‐structured interviews, which allowed for a more in‐depth analysis of the students' experiences with the VoiceBot. The results showed that how the VoiceBot was applied positively influenced student learning in the experimental cohort. Moreover, the focus group data demonstrated that the VoiceBot can be a valuable assistant for students and could be easily replicated in other courses. To the best of our knowledge, this study was the first to use VoiceBot to engage undergraduate students in Ghana, thus contributing to the growing literature stream on the development of VoiceBots to improve student learning experiences. This study elucidates the design process using a zero‐coding technique, which is considered a suitable approach for educational institutions with limited resources.Practitioner notesWhat is already known about this topic Conversational user interfaces (CUIs), including voice interfaces, have gained popularity and are used to interact with computers through natural language. VoiceBots have been utilised in various fields such as customer service to automate tasks and reduce redundancy. Instant messaging systems such as WhatsApp and Telegram have been used for communication in educational contexts. Advances in artificial intelligence (AI) and natural language processing (NLP) have led to significant improvements in voice‐enabled CUIs (VoiceBots). Existing studies indicate that chatbots affect students' motivation, learning experiences, and achievements; however, research on using VoiceBots for learning improvement is limited. What this paper adds A VoiceBot was introduced as an assistant to facilitate learning in a multimedia programming course. The study used an experimental design with an experimental cohort using a WhatsApp group platform equipped with a zero‐coding VoiceBot and a control cohort without the bot. The study found that students interacting with VoiceBot demonstrated better learning achievement than the control group. The study also provides clear suggestions on integrating VoiceBots into educational institutions. Implications for practice and/or policy The study's findings suggest that VoiceBots can play a significant role in improving student learning achievements, especially in subjects such as multimedia programming. Educational institutions could establish learning design and technology centres with subject matter experts to integrate VoiceBots effectively into the learning process. Instructors must possess adequate technological proficiency to engage students with VoiceBots and targeted in‐service training may be necessary. Future research can explore VoiceBot use across various academic domains and levels of education, analyse the impact of usage patterns on learning outcomes, and assess its long‐term effects on student engagement and motivation.
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来源期刊
British Journal of Educational Technology
British Journal of Educational Technology EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
15.60
自引率
4.50%
发文量
111
期刊介绍: BJET is a primary source for academics and professionals in the fields of digital educational and training technology throughout the world. The Journal is published by Wiley on behalf of The British Educational Research Association (BERA). It publishes theoretical perspectives, methodological developments and high quality empirical research that demonstrate whether and how applications of instructional/educational technology systems, networks, tools and resources lead to improvements in formal and non-formal education at all levels, from early years through to higher, technical and vocational education, professional development and corporate training.
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