Level-Up your Learning – Introducing a Framework for Gamified Educational Conversational Agents

Driven by circumstances like the global pandemic many learners and educators realize the importance and value of self-regulated digital learning. To better support self-regulated learning, conversational agents have become more relevant. Conversational agents can act as tutor or as learning mate for learners. Although conversational agents have potential to better support self-regulated learning processes, challenges exist requiring implications about how to make these interactions more engaging and supportive. This study discusses the value of gamified conversational learning chatbots that use game elements to engage learners to guide researchers and practitioners to design conversational agents that effectively motivate learners and provide self-regulated learning at the same time. Therefore, we propose a systematically developed framework for gamifying educational conversational agents and contribute to theory by consolidating several theories about games, digital learning, and conversational agents and support practitioners by providing implications about what to care about when gamifying conversational agents

Game-inspired Pedagogical Conversational Agents: A Systematic Literature Review

Pedagogical conversational agents (PCAs) are an innovative way to help learners improve their academic performance via intelligent dialog systems. However, PCAs have not yet reached their full potential. They often fail because users perceive conversations with them as not engaging. Enriching them with game-based approaches could contribute to mitigating this issue. One could enrich a PCA with game-based approaches by gamifying it to foster positive effects, such as fun and motivation, or by integrating it into a game-based learning (GBL) environment to promote effects such as social presence and enable individual learning support. We summarize PCAs that are combined with game-based approaches under the novel term “game-inspired PCAs”. We conducted a systematic literature review on this topic, as previous literature reviews on PCAs either have not combined the topics of PCAs and GBL or have done so to a limited extent only. We analyzed the literature regarding the existing design knowledge base, the game elements used, the thematic areas and target groups, the PCA roles and types, the extent of artificial intelligence (AI) usage, and opportunities for adaptation. We reduced the initial 3,034 records to 50 fully coded papers, from which we derived a morphological box and revealed current research streams and future research recommendations. Overall, our results show that the topic offers promising application potential but that scholars and practitioners have not yet considered it holistically. For instance, we found that researchers have rarely provided prescriptive design knowledge, have not sufficiently combined game elements, and have seldom used AI algorithms as well as intelligent possibilities of user adaptation in PCA development. Furthermore, researchers have scarcely considered certain target groups, thematic areas, and PCA roles. Consequently, our paper contributes to research and practice by addressing research gaps and structuring the existing knowledge base

Chatbot as a learning assistant: Factors influencing adoption and recommendation

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceSoon, it is expected that artificial intelligence (AI) may replace many jobs whose work is based in repetitive tasks. Considering the role that this technology will play in our lives over the next few years, it would be interesting to take advantage of its potential now and use it as a transformation agent in the educational system. This study aims to evaluate the main drivers for adoption and recommendation of chatbots as a learning assistant to students in higher education. The research uses an innovative model based on gamification affordance, support construct from the students control model, and performance expectance, hedonic motivation, and behavioural intention to adopt constructs from the well-known UTAUT2 model. The model was empirically assessed using structural equation modelling (SEM) based on 302 responses from an online survey conducted in a South American country, Brazil. Support and hedonic motivation were found to be the most significant drivers for behaviour intention to adopt a chatbot. To explain the antecedents of the intention to recommend a chatbot, support and behavioural intention to adopt were the most important drivers found. For scholars, this research brings new material for further exploration of individual drivers for technology adoption and recommendation. For practitioners, knowing the main drivers for adoption and recommendation of a chatbot enables them to develop a technology with higher chances of absorption in the market

Impact of artificial intelligence on education for employment: (learning and employability Framework)

Sustainable development has been a global goal and one of the key enablers to achieve the sustainable development goals is by securing decent jobs. However, decent jobs rely on the quality of education an individual has got, which value the importance of studying new education for employment frameworks that work. With the evolution of artificial intelligence that is influencing every industry and field in the world, there is a need to understand the impact of such technology on the education for employment process. The purpose of this study is to evaluate and assess how AI can foster the education for employment process? And what is the harm that such technology can brings on the social, economical and environmental levels? The study follows a mapping methodology using secondary data to identify and analyze AI powered startups and companies that addressed the learning and employability gaps. The study revealed twelve different AI applications that contribute to 3 main pillars of education for employment; career exploration and choice, skills building, and job hunting. 94% of those applications were innovated by startups. The review of literature and study results showed that AI can bring new level of guidance for individuals to choose their university or career, personalized learning capabilities that adapt to the learner\u27s circumstance, and new whole level of job search and matchmaking

O contexto da investigação em inteligência artificial e gamificação para melhorar o envolvimento e a assiduidade dos estudantes no ensino superior

A significant concern that is widely discussed in the field of Higher Education is declining student participation. In several institutions, attendance is optional, allowing students to attend lectures at their convenience. This study proposes the integration of Artificial Intelligence and Gamification to improve student engagement and attendance rates. The initiative combines advanced technological strategies with conventional educational methodologies to enhance the lecture experience. The initiative is significant as formal lectures often witness dwindling student interest and frequent absenteeism, undermining the educational process and student's future career prospects. This combination has the potential to revolutionise Higher Education by providing a more interactive and engaging learning experience. While gamification has positively impacted learning in various contexts, integration with Artificial Intelligence is a game-changer, paving the way for a modernised educational experience. This innovative exploration of the AI-gamification blend sets the stage for future research and the implementation of updated academic strategies, ultimately addressing student engagement and attendance. This position paper presents the bases and foundations for understanding the problem of student attendance and engagement and the role of AI and gamification in Higher Education in alleviating it.Uma inquietação relevante e extensamente discutida no domínio do Ensino Superior é a diminuição da participação dos estudantes. Em diversas instituições, a assiduidade é facultativa, permitindo aos estudantes a frequência às aulas segundo a sua disponibilidade. Este estudo propõe a integração da Inteligência Artificial e da Gamification como meios para melhorar o envolvimento e as taxas de assiduidade dos estudantes. A iniciativa em causa articula estratégias tecnologicamente avançadas com metodologias educativas convencionais no intuito de enriquecer a experiência de ensino. Tal iniciativa assume importância dada à constante diminuição do interesse dos estudantes e a assiduidade irregular nas aulas formais, fatores que afetam negativamente o processo de ensino e as perspetivas de carreira dos estudantes. Esta combinação ostenta o potencial de revolucionar o Ensino Superior, proporcionando uma experiência de aprendizagem mais interativa e envolvente. Embora a Gamification já tenha impactado positivamente o processo de aprendizagem em diversos contextos, a sua integração com a Inteligência Artificial surge como um elemento transformador, abrindo caminho para uma experiência educacional modernizada. Esta investigação inovadora que combina a IA e Gamification prepara as bases para investigações futuras e a implementação de estratégias académicas aprimoradas, concentrando-se principalmente no envolvimento e na assiduidade dos estudantes. Este artigo de posicionamento apresenta as bases e os fundamentos necessários para a compreensão do problema da frequência e envolvimento dos estudantes no Ensino Superior, assim como o papel da IA e da Gamification na sua mitigação.info:eu-repo/semantics/publishedVersio

Design Knowledge for Virtual Learning Companions from a Value-centered Perspective

The increasing popularity of conversational agents such as ChatGPT has sparked interest in their potential use in educational contexts but undermines the role of companionship in learning with these tools. Our study targets the design of virtual learning companions (VLCs), focusing on bonding relationships for collaborative learning while facilitating students’ time management and motivation. We draw upon design science research (DSR) to derive prescriptive design knowledge for VLCs as the core of our contribution. Through three DSR cycles, we conducted interviews with working students and experts, held interdisciplinary workshops with the target group, designed and evaluated two conceptual prototypes, and fully coded a VLC instantiation, which we tested with students in class. Our approach has yielded 9 design principles, 28 meta-requirements, and 33 design features centered around the value-in-interaction. These encompass Human-likeness and Dialogue Management, Proactive and Reactive Behavior, and Relationship Building on the Relationship Layer (DP1,3,4), Adaptation (DP2) on the Matching Layer, as well as Provision of Supportive Content, Fostering Learning Competencies, Motivational Environment, and Ethical Responsibility (DP5-8) on the Service Layer

Towards Conversational Co-Creation of Learning Content in Digital Higher Education

Today formal education like higher education relies on digital learning content like learning videos or quizzes. Using such online learning material enables students to learn independently from time and place. While improvements have been made, there are still many issues as the two-year long crisis in 2020 has revealed. Many offerings do not consider the learners’ needs and can result in unsuccessful learning. One way to address these short comings is to actively include learners in the creation process of learning content. However, co-creation oftentimes relies on face to face and or group settings that may not be possible for all students at all times. Therefore, we undertake a long-term action design research project to investigate the novel concept of conversational co-creation of learning material using a conversational agent and persuasive design to engage and motivate learners. In this article we present an early-stage prototype and concept of conversational co-creation

AI in Student as Manager Model Future Directions of Business Studies

In the business programs of Universiti Pendidikan Sultan Idris (UPSI), the Three-Pronged teaching technique is implemented as a student-centered learning process. This approach combines elements of the game, problem, and challenge-based learning with the larger goal of preparing business students to handle complicated, unanticipated global or industrial problems. It promotes an interactive and dependable classroom that calls for students' innovative contributions, teamwork, and participation in the professional world. Micro credential platforms, artificial intelligence, and a new pedagogical strategy: that's the idea for UPSI's undergraduate business. Therefore, this kind of instruction is increasingly being used in business courses like Strategic Management. Undergraduate students benefit from this teaching method since they are exposed to industrial phenomena while developing 21st- century abilities (collaborative, creative, critical thinking, and communication)