The TA Framework: Designing Real-time Teaching Augmentation for K-12 Classrooms

Recently, the HCI community has seen increased interest in the design of teaching augmentation (TA): tools that extend and complement teachers' pedagogical abilities during ongoing classroom activities. Examples of TA systems are emerging across multiple disciplines, taking various forms: e.g., ambient displays, wearables, or learning analytics dashboards. However, these diverse examples have not been analyzed together to derive more fundamental insights into the design of teaching augmentation. Addressing this opportunity, we broadly synthesize existing cases to propose the TA framework. Our framework specifies a rich design space in five dimensions, to support the design and analysis of teaching augmentation. We contextualize the framework using existing designs cases, to surface underlying design trade-offs: for example, balancing actionability of presented information with teachers' needs for professional autonomy, or balancing unobtrusiveness with informativeness in the design of TA systems. Applying the TA framework, we identify opportunities for future research and design.Comment: to be published in Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 17 pages, 10 figure

Augmenting Education: Ethical Considerations for Incorporating Artificial Intelligence in Education

Artificial intelligence (AI) has existed in theory and practice for decades, but applications have been relatively limited in most domains. Recent developments in AI and computing have placed AI-enhanced applications in various industries and a growing number of consumer products. AI platforms and services aimed at enhancing educational outcomes and taking over administrative tasks are becoming more prevalent and appearing in more and more classrooms and offices. Conversations about the disruption and ethical concerns created by AI are occurring in many fields. The development of the technology threatens to outpace academic discussion of its utility and pitfalls in education, however. Conversations about the disruption and ethical concerns created by AI are occurring in many fields. To ensure that AI in education serves learners and educators and that ethical concerns are answered or mitigated, the field must first clarify what those concerns are. This paper surveys academic and trade literature and draws upon a parallel questionnaire deployed to define existing and emerging ethical concerns of AI in education

Education in the age of Generative AI: Context and Recent Developments

With the emergence of generative artificial intelligence, an increasing number of individuals and organizations have begun exploring its potential to enhance productivity and improve product quality across various sectors. The field of education is no exception. However, it is vital to notice that artificial intelligence adoption in education dates back to the 1960s. In light of this historical context, this white paper serves as the inaugural piece in a four-part series that elucidates the role of AI in education. The series delves into topics such as its potential, successful applications, limitations, ethical considerations, and future trends. This initial article provides a comprehensive overview of the field, highlighting the recent developments within the generative artificial intelligence sphere

Rethinking Education in the Age of AI: The Importance of Developing Durable Skills in the Industry 4.0

This article discusses the pressing need to integrate artificial intelligence (AI) into education to facilitate customizable, individualized, and on-demand learning pathways. At the same time, while AI has the potential to expand the learner base and improve learning outcomes, the development of NACE Competencies and durable skills – communication, critical thinking, creativity, leadership, adaptability, and emotional intelligence - must be purposefully integrated in curriculum design now more than ever. Recent studies have shown that AI-driven learning pathways can achieve outcomes more quickly, but this comes at the cost of the development of durable skills. Therefore, traditional student-to-student and student-to-teacher interactions must be prioritized. As such, this study proposes a balanced approach to curriculum design to ensure the best outcomes for learners, where durable skill development is prioritized alongside subject-specific skills and rote memorization. Additionally, the article highlights the need for a combination of Just in Time Training (JITT) approaches, facilitated by AI technology, to reach the implementation of durable skills. The article concludes by questioning how to develop human skills in an increasingly AI-driven education system and emphasizes the importance of curriculum design and traditional learning approaches in creating a cohesive learning experience that develops durable skills in students. It is necessary to recognize that AI-driven education cannot replace the development of human skills, and that traditional interactions play a crucial role in developing these skills

Navigating the Use of ChatGPT in Classrooms: A Study of Student Experiences

Amidst growing concerns about ChatGPT-facilitated academic misconduct, universities are grappling with laying out clear guidelines, leaving students and academics in a state of confusion. In this milieu, the study delves into students\u27 perspectives to investigate their engagement with ChatGPT thus far, using Grounded Theory Method to analyze their behavior. Our findings reveal that ChatGPT can significantly enhance learning experiences when used appropriately. The tool\u27s conversational abilities allow students to tailor their interactions, fostering personalized learning and promoting inclusivity. However, a multitude of factors, including sociocultural influences, academic context-driven skepticism, and the tool\u27s limitations, shape students\u27 interactions with ChatGPT. Our study highlights the opportunities ChatGPT presents for technology-enhanced learning while acknowledging the challenges it poses to the academic landscape, paving the way for better-informed policies on the use of AI in higher education

Location-based and contextual mobile learning. A STELLAR Small-Scale Study

This study starts from several inputs that the partners have collected from previous and current running research projects and a workshop organised at the STELLAR Alpine Rendevous 2010. In the study, several steps have been taken, firstly a literature review and analysis of existing systems; secondly, mobile learning experts have been involved in a concept mapping study to identify the main challenges that can be solved via mobile learning; and thirdly, an identification of educational patterns based on these examples has been done. Out of this study the partners aim to develop an educational framework for contextual learning as a unifying approach in the field. Therefore one of our central research questions is: how can we investigate, theorise, model and support contextual learning

The AI Revolution in Education: Will AI Replace or Assist Teachers in Higher Education?

This paper explores the potential of artificial intelligence (AI) in higher education, specifically its capacity to replace or assist human teachers. By reviewing relevant literature and analysing survey data from students and teachers, the study provides a comprehensive perspective on the future role of educators in the face of advancing AI technologies. Findings suggest that although some believe AI may eventually replace teachers, the majority of participants argue that human teachers possess unique qualities, such as critical thinking, creativity, and emotions, which make them irreplaceable. The study also emphasizes the importance of social-emotional competencies developed through human interactions, which AI technologies cannot currently replicate. The research proposes that teachers can effectively integrate AI to enhance teaching and learning without viewing it as a replacement. To do so, teachers need to understand how AI can work well with teachers and students while avoiding potential pitfalls, develop AI literacy, and address practical issues such as data protection, ethics, and privacy. The study reveals that students value and respect human teachers, even as AI becomes more prevalent in education. The study also introduces a roadmap for students, teachers, and universities. This roadmap serves as a valuable guide for refining teaching skills, fostering personal connections, and designing curriculums that effectively balance the strengths of human educators with AI technologies. The future of education lies in the synergy between human teachers and AI. By understanding and refining their unique qualities, teachers, students, and universities can effectively navigate the integration of AI, ensuring a well-rounded and impactful learning experience

Exploring the ethical considerations of using Chat GPT in university education

This study investigates the moral dilemmas that arise with incorporating Chat GPT into higher education, with a focus on the situation in Latinoamerican institutions of higher learning. The study surveyed 220 people via online questionnaire to learn more about their experiences with and motivations for using AI-powered conversational agents. An overview of the demographics of the participants was provided through descriptive statistics. This investigation of the subject at hand lays the groundwork for further research. It also reveals the hidden meanings of the observed phenomena, and it suggests possible solutions to the problems that have been uncovered. This research looks at how AI systems and chatbots can supplement human knowledge and judgment, as well as their potential drawbacks. The results showed that participants thought Chat GPT integration was moderately accessible and had moderately positive social attitudes. They understood the value and responsibility of Chat GPT in creating individualized educational opportunities. Participants stressed the necessity for explicit institutional standards regarding privacy and data security. Gender, age, sense of accessibility, social attitude, opinions, and personal experience, privacy and data security, institutional guidelines, and individualized learning were also found to affect participants' reliance on AI through regression analysis. The findings shed light on how the integration of Chat GPT into Latinoamerican higher education is complicated by factors such as individual beliefs, cultural norms, and ethical problems. The busy schedules of students may be accommodated and the resources they need to succeed can be made available thanks to this adaptability. In addition, natural language processing models can offer students instantaneous help via text chat, voice, or video. To fully grasp the ethical consequences and lead the creation of responsible implementation techniques, the research proposes that additional qualitative investigations, longitudinal studies, and comparative research across diverse contexts is required. Closing these knowledge gaps will help move the conversational AI field forward in ways that are ethical and beneficial to the classroom