2,437 research outputs found
Protecting Privacy in Indian Schools: Regulating AI-based Technologies' Design, Development and Deployment
Education is one of the priority areas for the Indian government, where Artificial Intelligence (AI) technologies are touted to bring digital transformation. Several Indian states have also started deploying facial recognition-enabled CCTV cameras, emotion recognition technologies, fingerprint scanners, and Radio frequency identification tags in their schools to provide personalised recommendations, ensure student security, and predict the drop-out rate of students but also provide 360-degree information of a student. Further, Integrating Aadhaar (digital identity card that works on biometric data) across AI technologies and learning and management systems (LMS) renders schools a âpanopticonâ.
Certain technologies or systems like Aadhaar, CCTV cameras, GPS Systems, RFID tags, and learning management systems are used primarily for continuous data collection, storage, and retention purposes. Though they cannot be termed AI technologies per se, they are fundamental for designing and developing AI systems like facial, fingerprint, and emotion recognition technologies. The large amount of student data collected speedily through the former technologies is used to create an algorithm for the latter-stated AI systems. Once algorithms are processed using machine learning (ML) techniques, they learn correlations between multiple datasets predicting each studentâs identity, decisions, grades, learning growth, tendency to drop out, and other behavioural characteristics. Such autonomous and repetitive collection, processing, storage, and retention of student data without effective data protection legislation endangers student privacy.
The algorithmic predictions by AI technologies are an avatar of the data fed into the system. An AI technology is as good as the person collecting the data, processing it for a relevant and valuable output, and regularly evaluating the inputs going inside an AI model. An AI model can produce inaccurate predictions if the person overlooks any relevant data. However, the state, school administrations and parentsâ belief in AI technologies as a panacea to student security and educational development overlooks the context in which âdata practicesâ are conducted. A right to privacy in an AI age is inextricably connected to data practices where data gets âcookedâ. Thus, data protection legislation operating without understanding and regulating such data practices will remain ineffective in safeguarding privacy.
The thesis undergoes interdisciplinary research that enables a better understanding of the interplay of data practices of AI technologies with social practices of an Indian school, which the present Indian data protection legislation overlooks, endangering studentsâ privacy from designing and developing to deploying stages of an AI model. The thesis recommends the Indian legislature frame better legislation equipped for the AI/ML age and the Indian judiciary on evaluating the legality and reasonability of designing, developing, and deploying such technologies in schools
Leveraging robotics to enhance accessibility and engagement in mathematics education for vision-impaired students
There is potential to use robotics in education to revolutionize teaching and learning in mathematics. This is particularly relevant for vision-impaired students, who face different challenges when accessing mathematical content. Educational robotics can potentially enhance accessibility, motivation, and engagement in mathematics for students through enjoyable and novel interactions. Students commonly experience positive interactions with educational robots during learning activities, which influences their learning motivation. Recent studies show that students with disabilities face issues related to classroom participation, lack of collaborative learning, reduced social engagement, and potential for isolation. Digital-based learning technologies have transformed how vision-impaired students engage with and learn mathematics. Leveraging robotics in mathematics teaching and learning through personalised guidelines offers considerable benefits for vision-impaired students, including enhanced engagement, multimodal learning opportunities, and improved collaboration and communication skills, which enhances the opportunities for inclusive classroom experiences. This paper outlines the role of educational robotics in inclusive education. It examines the challenges and benefits of using educational robotics in mathematics for vision-impaired students. The importance of human-robot interaction (HRI) in steering the design and functionality of educational robots and their potential use within the classroom to facilitate learning is also highlighted
âSo what if ChatGPT wrote it?â Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy
Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPTâs capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPTâs use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts
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Design for Accessible Collaborative Engagement: Making online synchronous collaborative learning more accessible for students with sensory impairments.
This thesis looks at the accessibility of collaborative learning and the barriers to engagement experienced by blind/visually impaired (BVI) students and deaf/hard of hearing (DHH) students. It focuses specifically on online synchronous collaborative learning after establishing that this format presented the greatest barriers, and that these student groups were not engaging.
Taking a design-based research (DBR) approach, five studies were undertaken to identify these barriers and determine potential interventions. The product of the research, a result of collaborative design by the participants in the study, is a framework for accessible collaborative engagement represented in the form of an interactive website model, the Model for Accessible Collaborative Engagement (MACE).
The studies involved representatives of all stakeholders in the collaborative learning process at the institution (the Open University): students, tutors, modules teams, academics, support staff, and the student union Disabled Students Group. These studies took the form of an online survey of 327 students, 10 interviews with staff and students, 6 staff workshops and a collaborative design focus group. With significant representation of the target groups (BVI and DHH) in all studies, and taking an iterative approach to the design, evaluation and construction of the framework model, the studies established that barriers existed in four main categories covering different themes:
1. Communications: aural, visual, screen reading and navigation, text and captioning, lip reading and non-verbal communications, interpretation and third-party communications, mode control, and synchronisation.
2. Emotional and Social Factors: familiarisation, support networks, self-advocacy, opting out, cognitive load, and stress and anxiety.
3. Provisioning and Technical Factors: dissemination, speed and pacing of sessions, staff training, participation control, group size, technical provisioning, and recordings.
4. Activity and Session Design: Volume of materials, advance materials, accessible materials, accessible activities, and session formats.
Interventions were designed that could reduce the barriers in each of these categories and themes by adjustments and changes from both the student and institutional standpoints. MACE is designed to be utilised by both students and staff to provide guidance and suggestions on how to identify and acknowledge these barriers and implement interventions to reduce them.
This research represents an original and essential contribution to the field of investigation. As well as informing future research inquiry, the model can be used by all participants and stakeholders in online collaborative learning to help reduce barriers for BVI and DHH students and improve inclusivity in synchronous online events
Mission Focus: Supporting executive functions in VLEs and the design of inclusive user interfaces.
Virtual learning environments (VLEs)âŻuse educational technologies to facilitate remote online learning in the absence of synchronous supervision and support. Most VLEs offer inclusive options for learners to access content at any time and to adapt content into a form suiting their interaction modes. They also facilitate online collaboration and peer communication. However, they do not fully consider the needs of pre-literate adolescents with developing executive functioning for engaging in asynchronous learning, resulting in barriers. Through an exploratory-cum-participatory research approach combined with a collaborative and iterative co-design process with the participants, this study explored and examined barriers to independent and asynchronous functions that pre-literate adolescent learners face when learning in a VLE, such as planning, focus, and setting and achieving goals (executive functions). Building on principles for user interface design, guidelines were developed to help enhance the design of VLEs to make them more inclusive of diverse executive functioning needs
Machine Learning Clustering Analysis Towards Educatorâs Readiness to Adopt Augmented Reality as a Teaching Tool
The advanced digital revolution has shifted conventional teaching and learning into digital education. In consistency with digital education, Augmented Reality (AR) applications started to shine in the education industry for their ability to create conducive teaching and learning environments, especially in remote learning during the COVID-19 pandemic. Movement Control Order (MCO) implemented in the year 2020 has led to emergency remote teaching and learning without much preparation for all educators and learners. Throughout these few years, most educators got familiar with digital teaching tools and online teaching platforms. Hence, this study aims to explore educatorsâ readiness to adopt AR as a teaching tool in their teaching during the endemic period. A quantitative approach via questionnaire has been distributed to the Private Higher Education Institutions (PHEIs) in the states of Selangor and Kuala Lumpur. Machine learning using a clustering technique was used to find patterns between the demographics of educators towards the AR perception of educators. The results revealed that educators' perceptions of AR technology are influenced by their familiarity with it, their personal beliefs, and their attitudes toward technology. This study provides an insightful overview of the benefits of AR applications in education and the implications of the adoption of AR in Malaysian schools and educational institutions. It also highlights the importance of motivating educators and students to embrace AR as an enhancement learning tool, providing a valuable discussion for the government, learning institutions, and educators on the implementation of AR in Malaysia
Thematic Working Group 3 - Inclusion of Excluded Populations : Access and Learning Optimization via IT in the Post-Pandemic Era
Thematic Working Group (TWG) 3âs theme is âInclusion of excluded populations: access and learning optimization via IT in the post-pandemic eraâ. A focal concern is established by the presence of the first word â âinclusionâ â and how this relates to âexcluded populationsâ. Much of the research in this field has focused on inclusion for individuals; however, the evidence shows that educational exclusion has multiple dimensions (Passey, 2014). To accommodate this within the current focus, therefore, identifying key dimensions of âexcluded populationsâ will be a key concern of this document. âAccessâ will be considered beyond physical technology access, involving aspects of accessibility, agency and empowerment. These aspects relate to a definition of access that concerns the needs for individuals to develop and have digital capabilities and abilities to select applications appropriate to purpose, as discussed, for example, by Helsper (2021) and Passey et al. (2018). Taking this wider concern for access, âlearning optimizationâ will be explored as a term that highlights the need to focus on technological access and provision enabling successful outcomes. Given the fact that the intention of the work of TWG3 is to explore findings in the âpost-pandemicâ context, communication technologies as well as just information technology, âITâ, are clearly important and need to be considered. Additionally, exclusion factors to be addressed need to be clearly identified so that inclusion can be accommodated and ensured in the context of specific excluded populations. However, inclusion should not be implemented as an imposition in the context of digital technologies, as some populations do not wish to use digital technologies (Wetmore, 2007), and in this respect the issue of the need to acknowledge diversity is important
A Closer Look into Recent Video-based Learning Research: A Comprehensive Review of Video Characteristics, Tools, Technologies, and Learning Effectiveness
People increasingly use videos on the Web as a source for learning. To
support this way of learning, researchers and developers are continuously
developing tools, proposing guidelines, analyzing data, and conducting
experiments. However, it is still not clear what characteristics a video should
have to be an effective learning medium. In this paper, we present a
comprehensive review of 257 articles on video-based learning for the period
from 2016 to 2021. One of the aims of the review is to identify the video
characteristics that have been explored by previous work. Based on our
analysis, we suggest a taxonomy which organizes the video characteristics and
contextual aspects into eight categories: (1) audio features, (2) visual
features, (3) textual features, (4) instructor behavior, (5) learners
activities, (6) interactive features (quizzes, etc.), (7) production style, and
(8) instructional design. Also, we identify four representative research
directions: (1) proposals of tools to support video-based learning, (2) studies
with controlled experiments, (3) data analysis studies, and (4) proposals of
design guidelines for learning videos. We find that the most explored
characteristics are textual features followed by visual features, learner
activities, and interactive features. Text of transcripts, video frames, and
images (figures and illustrations) are most frequently used by tools that
support learning through videos. The learner activity is heavily explored
through log files in data analysis studies, and interactive features have been
frequently scrutinized in controlled experiments. We complement our review by
contrasting research findings that investigate the impact of video
characteristics on the learning effectiveness, report on tasks and technologies
used to develop tools that support learning, and summarize trends of design
guidelines to produce learning video
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