Digital Education Review

Editorial: Artificial intelligence from educability

Cristina Galván Fernández — 2024-07-01

AI in the discourse of the relationships between technology and education

José Luis Rodríguez Illera — 2024-07-01

The article reviews some of the relationships between AI and education, emphasizing the metaphors used, the difficulties in finding points of agreement, as well as aspects of the social criticism that is made of AI (e.g. considering that it can be a form of unwanted deviation). AI appears as one more case of technology that comes to improve education, as happened in the past with other less “intelligent” technologies, although now with more arguments in its favor. Secondly, it explores the logical mechanisms (abduction) that are widely used in human reasoning but also in AI, showing how their uncontrolled use can lead to certain conversation algorithms being able to lie, something that teachers would not do. An ethical rather than logical question is raised that deserves to be explored later.

From Educability to Technology Acceptability and Artificial Intelligence Literacy: Validation of an Instrument

Cristina Galván Fernández — 2024-07-01

In the first wave of AI, Susan Leigh Star made visible how the development of AI was done without social consensus by considering Davis' studies in relation to the acceptance of technology in the world of work. The conclusions derived, known as the Durkheim test, respond to the antonyms that are being formulated during the settlement of AI in educational discourses. Recognising that the act of educating today is nourished from the most libertarian pedagogies to those more driven by political agendas, there are multiple educational perspectives in relation to AI. In this diversity, the different fields of educational action may or may not adopt AI from an instrumental and/or social perspective. Despite the topicality of the subject, researchers are still lacking instruments to analyse the positions of the educational community in general and of the student stratum in particular. For this reason, the aim of this article is to adapt and validate two surveys that have shown excellent results in their original versions, as well as to analyse the relationship between the two. For this purpose, the adaptation of the technology acceptance survey and the AI literacy survey has been applied to a sample of 134 students from different Masters in Education programmes. The exploratory factor analysis and the subsequent confirmatory factor analysis have shown the validity of the adapted instrument.

Artificial Intelligence: Educational tensions between truth and data verisimilitude

Carles Lindín — 2024-07-01

Elements of analysis that are operative for a critical incorporation of generative and non-generative artificial intelligences (AI) are pointed out. Approaching a balanced digital pedagogical realism in which AI can enhance individual and collective educational spaces instead of generating overproduction. The focus is on relevant pedagogical reflections, taking into account the regulatory needs of AIs. AIs are characterized, starting with a brief analysis of the social, educational and economic environment in which they are widely disseminated. The necessary framework is presented to examine various tensions that they incorporate into the educational ecosystem, which have their origin in the truth-verisimilitude-fiction value provided by data. Four spaces of tension provoked by the massive advent of AIs in education are discussed: authorship, verisimilitude spiral (or truth-value), fiction and literariness, datafication and agency. As a result, it emerges that it is appropriate to consider the impact of AIs on teaching-learning processes in terms of the more or less distant relationship they may have with material reality: their ability to create fictional narratives based on real data.

Philosophical, ethical and pedagogical implications of the use of Artificial Intelligence in education

Raúl Arango Pérez — 2024-07-01

This article examines the philosophical, ethical and pedagogical implications of the use of Artificial Intelligence (AI) in education. In this way, and starting from the diversity of opinions on the potential of AI in this field, ranging from enthusiastic perspectives to alarmist predictions, this study proposes a critical and exploratory analysis of these implications through a hermeneutic approach that considers different relevant perspectives in order to evaluate and guide the use of AI in education and its potential impact on the pedagogical relationship, betting on the humanisation of technology and avoiding the technologisation of humans. The ultimate purpose is to better understand the challenges and opportunities presented by the convergence of AI and education, and to promote a competent and conscious use of these technologies, especifically on terms of Teacher-Student Relationship.

Systematic review of trends in the application of artificial intelligence to the field of academic writing in the social sciences

Francesc Martínez-Olmo — 2024-07-01

The study of the application of artificial intelligence (AI) in academic writing is important to promote efficiency in the generation of scientific content. Additionally, there is a need to investigate how AI can help improve the clarity and accuracy of scientific communication. In this sense, a systematic review of the literature (scoping review) has been carried out that has addressed the use of AI, specifically ChatGPT, in relation to academic writing. The objective is to identify the thematic approaches and inquiry designs applied in the works published on this topic and, thus, guide future projects in this line of research. To carry out this study, we proceeded to locate articles in Web of Science and Scopus. The main results of the work reveal the interest in academic writing and AI in relation to its possible applications, specific tools and the detection of plagiarism, as well as its ethical and responsible use. Besides, this study stated the application of various research methods. The final discussion focuses on how the integration of AI in academic writing poses both opportunities and challenges in terms of ethics, quality and intellectual autonomy.

Impact of Digital Literacy, Use of AI tools and Peer Collaboration on AI Assisted Learning- Perceptions of the University students

Genimon Vadakkemulanjanal Joseph — 2024-07-01

The technology-supported education systems seamlessly integrated throughout the globe in response to the challenges posed by the Covid-19 pandemic. The swift developments of the digital tools with Artificial Intelligence (AI) support are also readily diffused among the educational communities. This research paper investigates the synergistic impact of digital literacy, the incorporation of AI tools, and Peer Supported Collaborative Learning (PSCL) on the learning perceptions of university students. The research aims to discern the implications of these technological and social facets on students' attitudes towards AI assisted learning process. Structured questionnaire-based survey among the University students were done for this descriptive research. 409 responses collected were analysed with SPSS, Excel and Process Macro. It is found that the students’ Digital Literacy, Use of AI tools and PSCL on AI assisted learning were positively correlated. The partial mediatory path through the PSCL and AI tool usage has a significant positive influence on students learning process. The insights gathered from this study can inform educators, policymakers, and institutions on optimizing the amalgamation of digital literacy, AI tools and PSCL to enhance the contemporary learning environment. As universities navigate the digital age, this research provides a nuanced understanding of the dynamics shaping students' perceptions, offering valuable insights into the multifaceted aspects of AI influencing the educational landscape

Can Artificial Intelligence help provide more sustainable feed-back?

Eloi Puertas Prats — 2024-07-01

Peer assessment is a strategy wherein students evaluate the level, value, or quality of their peers' work within the same educational setting. Research has demonstrated that peer evaluation processes positively impact skill development and academic performance. By applying evaluation criteria to their peers' work and offering comments, corrections, and suggestions for improvement, students not only enhance their own work but also cultivate critical thinking skills. To effectively nurture students' role as evaluators, deliberate and structured opportunities for practice, along with training and guidance, are essential.

Artificial Intelligence (AI) can offer a means to assess peer evaluations automatically, ensuring their quality and assisting students in executing assessments with precision. This approach allows educators to focus on evaluating student productions without necessitating specialized training in feedback evaluation.

This paper presents the process developed to automate the assessment of feedback quality. Through the utilization of feedback fragments evaluated by researchers based on pre-established criteria, an Artificial Intelligence (AI) Large Language Model (LM) was trained to achieve automated evaluation. The findings show the similarity between human evaluation and automated evaluation, which allows expectations to be generated regarding the possibilities of AI for this purpose. The challenges and prospects of this process are discussed, along with recommendations for

optimizing results.

Artificial intelligence can offer a means to assess peer evaluations automatically, ensuring their quality and assisting students in executing assessments with precision. This approach allows educators to focus on evaluating student productions without necessitating specialized training in feedback evaluation.

This paper presents the process developed to automate the assessment of feedback quality. Through the utilization of feedback fragments evaluated by researchers based on pre-established criteria, an artificial intelligence Large Language Model was trained to achieve automated evaluation. The challenges and prospects of this process are discussed, along with recommendations for optimizing results.

Bridging Motivation and AI in Education: An Activity Theory Perspective

Inna Artemova — 2024-07-01

After the pandemic, research on Artificial Intelligence (AI) in the field of education has seen a significant increase globally. Although this topic is not new to education, very few studies conducted before the pandemic addressed the problem of supporting internal motivation in students, crucial for the quality of learning and knowledge retention. This study explores the extent to which this topic is covered in recent research by conducting a cross-disciplinary literature review within the theoretical framework of Activity Theory (AT). It aims to identify the extent of coverage of all types of relationships between nodes in the educational activity system, with special attention to Subject (students) and Object, as this central relationship embodies the motive-driven nature of human activity. The analysis incorporated 69 articles from Scopus published from 2020 till present. The results demonstrate coverage of only some relationships: Subject-Tools (students interaction with AI technology), Tools-Object (development of AI technologies), Tools-Community (adapting AI within an educational community). The central relationship between Subject and Object remains unexplored. Practical implications involve developing and integrating AI tools to stimulate intrinsic motivation by emphasizing personal meaning. Theoretical outcomes involve exploring how to foster and sustain students' intrinsic motivation in relation to AI.

Analyzing teacher candidates' arguments on AI integration in education via different chatbots

Volkan Duran — 2024-07-01

The burgeoning role of Artificial Intelligence (AI) in education prompts crucial discussions regarding its implications for teaching and learning. This qualitative study probes the argumentative perspectives of 118 teacher candidates from Iğdır University on the integration of AI into educational practices. Employing Toulmin's (1958) model, we analyzed their arguments, which encompass claims, evidence, warrants, backings, rebuttals, and conclusions, to ascertain their stance on AI's pedagogical integration. Utilizing four distinct AI chatbots—GPT-4, Gemini AI, Claude 3 Haiku, and Mistral AI—the research deciphers thematic undercurrents within these dimensions. Moreover, a novel methodological contribution is made through 'negative space exploration', focusing on the unmentioned themes to identify latent biases and assumptions in the argumentation. The study's dual analytical approach, combining AI-driven theme identification and negative space exploration, resulted in an enriched understanding of the content. Key findings suggest a nuanced perception among participants: while AI chatbots are acknowledged for enhancing educational efficiency and enabling personalized learning, concerns regarding diminished human interaction, potential erosion of critical thinking skills, and ethical use persist. The analyses also highlight the need for a balanced AI implementation that supports, not supplants, traditional educational methods. This research contributes to the ongoing debate on effective AI integration in education and calls for responsible pedagogical adoption of AI technologies.

The ARTificial Revolution: Challenges for Redefining Art Education

Andrés Torres Carceller — 2024-07-01

After years of development in the background, Artificial Intelligence (AI) has burst onto the global stage thanks to open tools for generating textual, visual, auditory, and audiovisual content. In this emerging context, AI is not only emerging as a technological phenomenon but also as a catalyst for innovation in the artistic and educational fields. Although we are only at the dawn, AI is rapidly evolving and leading us towards a revolution, opening a new field of possibilities in creative domains that will transform current aesthetic, procedural, and authorial conceptions. Its potential as a creative tool is currently limited to being a support that facilitates obtaining results of great formal quality and style quickly, but without human intervention based on clear objectives, it becomes an empty generator. Artistic Education must embrace this technology not as an intruder or rival, but as a tool to be known and integrated as another means of creation, developing skills that allow students not only to use these tools effectively but also to reflect on their implications in society and culture. Promoting a conscious, responsible, safe, and ethical use that ensures a critical stance towards generative AI. Understand that it is not a creative tool. It is for creators.

Creativity and artificial intelligence: A study with prospective teachers

Isabel Pont-Niclos — 2024-07-01

Artificial Intelligence (AI) brings enormous opportunities into learning, teaching, and assessment processes. Among them, it is convenient to explore its ability to channel students’ creativity, which is described as a basic competence in the training of people with both the OECD and the recent Spanish LOMLOE law pointing to the need to foster it in educational settings. In this context, the objective of this research is to explore the creative potential of prospective elementary school teachers related to storytelling, via a project including the rational use of AI generative tools. A combination of qualitative and quantitative instruments was used to get insight on the implications of those AI tools in the creative process and to gain understanding on the concerns of prospective teachers about AI at both their training and future teaching practice. The results show the potential of AI from an educational point of view, specially in self-assessment and co-evaluation processes, since it allows confronting not only the result of the creative task, but also the process itself by reflecting on the asked questions. Finally, the importance of continuing research on the ability to ask questions (a creative skill in itself) in the new context of AI is discussed.

Transforming and Reforming the Indian Education System with Artificial Intelligence

Prerna Sihag — 2024-07-01

India’s growing economy and population proves its significant stake in the Artificial lntelligence (AI) revolution. India's education and technology sector has grown exponentially over the last few years, particularly in times of Covid-19 pandemic but owing to various reasons, it is accessible to only one in four students in India. AI has proven to be of benefit to all stakeholders alike by (a) enhancing teachers' efficiency and effectiveness in managing Multi Levelled or Multi Graded Learning Units and enabling automated development of customised teaching content; (b) using Intelligent Tutoring Systems to tailor the learning materials to a child's level of competence, style and pace of learning for improving student interactivity and attention rates; and (c) for effective teacher posting and transfer systems and predicting likely student activities such as dropout rates in government schools. The research provides a comprehensive review of the rigorous inclusion of Al in India's education sector through various policy measures. According to the findings, Al increases the efficiency of grading and encourages critical thinking and analytical skills among students. Further studies can assess effective integration of AI with educational practices and policies to increase learning needs.

Communication Educators Facing the Arrival of Generative Artificial Intelligence: Exploration in Mexico, Peru, and Spain

Julio-César Mateus — 2024-07-01

This research explores university educators' perspectives on the opportunities, concerns, and considerations associated with Generative Artificial Intelligence (GenAI) in the training of professional communicators. Positioned at the early stages of ChatGPT's integration into educational settings, the study examines teachers' assignment instructions, assessments of ChatGPT's responses, and reflections on these outcomes. Employing a cross-sectional, qualitative methodology, the research involves a sample of 22 teachers from communication faculties in Mexico, Peru, and Spain. Utilizing Bloom’s taxonomy and an inductive approach for data analysis, the findings unveil nuanced views on GenAI's role in teaching practice. Teachers perceive ChatGPT as a tool with varying impacts depending on its application. They articulate distinct roles for ChatGPT, viewing it as either an ally or a rival, prompting discussions on anthropomorphizing technologies and emphasizing the need to empower students in GenAI tool usage, establish ethical protocols, and reconsider assessment methods, among other key considerations.

Teaching AI to the Next Generation: A Humanistic Approach

Anna Trifonova — 2024-07-01

This article proposes a comprehensive AI curriculum tailored for young learners aged 11 to 14, emphasizing a humanistic approach. We review other AI curricula proposals for children and young people and underline that they focus primarily on AI's technological benefits and on learning coding and logic. Our curriculum explores human cognition that is often overlooked in existing AI curriculum. Our proposal combines learning through construction, reflective discussions and project-based learning in order to approach AI from variety of angles. Implemented by CreaTIC Academy during 2023/24 school year as an out-of-school activity in a secondary (middle) school in Barcelona, Spain, this curriculum integrates technological, philosophical, cognitive, and cultural dimensions. It draws from diverse fields, including Philosophy of Mind, Cognitive Psychology and Philosophy of Children, and includes practical coding with tools like Scratch and AppInventor, as well as Machine Learning for Kids. Designed to be adaptable across various socio-economic contexts, our approach aims to promote a broader liberal education for children and help teachers implement AI activities in their classrooms.

Evaluating the evaluators: a comparative study of AI and Teacher Assessments in Higher Education

tugra karademir coskun — 2024-07-01

This study aims to examine the potential differences between teacher evaluations and artificial intelligence (AI) tool-based assessment systems in university examinations. The research has evaluated a wide spectrum of exams including numerical and verbal course exams, exams with different assessment styles (project, test exam, traditional exam), and both theoretical and practical course exams. These exams were selected using a criterion sampling method and were analyzed using Bland-Altman Analysis and Intraclass Correlation Coefficient (ICC) analyses to assess how AI and teacher evaluations performed across a broad range. The research findings indicate that while there is a high level of proficiency between the total exam scores assessed by artificial intelligence and teacher evaluations; medium consistency was found in the evaluation of visually-based exams, low consistency in video exams, high consistency in test exams, and low consistency in traditional exams. This research is crucial as it helps to identify specific areas where artificial intelligence can either complement or needs improvement in educational assessment, guiding the development of more accurate and fair evaluation tools.

Not all AI tools are created equal. Analysis of smart applications for university teaching

Manuel Area-Moreira — 2024-07-01

Currently, in addition to generative and conversational Artificial Intelligence (AI) applications or tools such as ChatGPT, Gemini, Perplexity, Copilot, Groq, and others, there exists a vast array of specific-purpose tools or apps for particular functionalities. These tools are continually evolving and are accessible through various repositories or web portals. In this article, we conducted a study of these apps with the objectives of: a) identifying and characterizing the AI tools specifically designed for the field of Higher Education, considering their functionality and didactic usability; and b) classifying the potential use of AI tools based on the phases of the teaching-learning process (pre-active, interactive, post-active) and the educational agents involved (teachers and students). For this purpose, 118 AI tools or apps created for educational purposes were selected from two of the most extensive international repositories or platforms (such as FUTUREPEDIA and THERE'S AN AI FOR THAT). A self-developed analysis instrument was used for their review. It is concluded that only a third of these tools are free, which presents an issue of inequality in access to them. Moreover, more than half have a dual function: to support both teaching (for teachers) and learning (for students).

Teacher professional development for a future with generative artificial intelligence – an integrative literature review

Anabela Brandão — 2024-07-01

Artificial Intelligence (AI) has been part of every citizen's life for several years. Still, the emergence of generative AI (GenAI), accessible to all, has raised discussions about the ethical issues they raise, particularly in education. GenAI tools generate content according to user requests, but are students using these tools ethically and safely? Can teachers guide students in this use and use these tools in their teaching activities? This paper argues that teacher professional development (TPD) is an essential key trigger in adopting these emerging technologies. The paper will present an integrative literature review that discusses the components of TPD that may empower teachers to guide their students towards the ethical and safe use of GenAI. According to the literature review, one key component of TPD should be AI literacy, which involves understanding AI, its capabilities and limitations, and its potential benefits and drawbacks in education. Another essential component is hands-on activities that engage teachers, their peers, and students in actively using these tools during the training process. The paper will discuss the advantages of working with GenAI tools and designing lesson plans to implement them critically in the classroom.

Development of AI Competencies for future teachers: A practical experience creating interactive narratives

Sara Cortés Gómez — 2024-07-11

Educational environments should implement the new technological models present in society. Among these, Artificial Intelligence (AI), for its pedagogical use and from the training of future teachers, who will teach these tools to the new generations. Therefore, the object of this work is to develop educational practices with student teachers to acquire basic skills in the understanding, practice and ethical use of AI.

This research presents an experience developed in a matter in Primary Education Degree where students have created interactive narratives using the Twine tool, as well as generative AI to enrich their stories. The data analysis focuses on examining the 10 stories created by the different working groups, as well as the creation process and the responses obtained to the final questionnaires, where we can understand the possibilities offered by AI, as well as the learning acquired by the students.

In conclusion, AI is being introduced in educational environments, therefore, training teachers will enable them to enhance their teaching and technological skills so that the teaching-learning process with their future students is meaningful and constructive.

Teachers' situated knowledge: Addressing digital exclusion in rural contexts

Isabel Pavez — 2024-07-01

This study delves into the intricate challenges surrounding incorporating information and communication technologies (ICTs) in education, particularly in regions characterized by digital exclusion, such as rural areas. By recognizing the potential of ICTs to support and expand student learning opportunities, this research explores the necessity for effective implementation through tailored professional development aligned with teachers' contextual conditions and needs. In addressing these challenges, the study explores the concept of technological appropriation, underscoring the significance of individual and contextual elements in adapting ICTs to users' specific needs and environments. Through unstructured face-to-face interviews with 21 teachers immersed in a digitally vulnerable rural context, this research unveils insights into how educators’ appropriate technologies to enhance student learning. The findings of this study contribute to the development of educational practices tailored to rural contexts, focusing on providing a meaningful and effective learning experience for students. By shedding light on teachers' strategies for navigating the digital landscape in challenging environments, the research aims to inform policies and practices that bridge the technological gap, ultimately fostering equitable access and enhanced educational outcomes in rural settings.

An exploration of agency enactment in e-portfolio learning co-design

Peng Zhang — 2024-07-01

Although research has always related e-portfolios to self-regulated learning, recently agency, which includes individual, relational, and contextual domains, has also been highlighted. Likewise, agency has been explored in technological environments that support collaborative and co-design learning processes. This study, investigating the enactment of student agency within e-portfolio learning co-design in secondary education, focuses on how students perceive their agency within a co-design e-portfolio learning framework, which was coined as the Co-PIRS model in previous stages of research. Among the findings, it can be argued that students report a greater awareness of agency, characterized by competence beliefs (individual domain) in the showcase phase of e-portfolios, peer learning (relational domain), and the opportunities to make choices (contextual domain) in the implementation phase. The study also reveals students' positive attitudes towards reflection, which suggests the suitability of structuring collaboration in the co-design approach. These insights serve as a foundation for implementing e-portfolio co-design frameworks to empower students’ agency and provide educators with guidance.

A Model of Assessment co-creation in Technology-Enhanced Learning Environments in Higher Education

Jennifer Saray Santana Martel — 2024-07-01

This paper presents a participatory design-based research that aimed to create a model of co-creation in the curriculum in Technology-Enhanced Learning Environments (TELE) in tertiary education, specifically to co-design assessment between professors and students. This qualitative research followed four phases divided into five stages with two iterative cycles of design and re-design. Accordingly, a mixed method approach was used to collect the data: systematic literature review, semi-structured interviews, and student surveys. As a result, the model highlights and distinguishes four different dimensions: characterization, co-creation, reflection, and technology. The first three dimensions are represented chronologically and the last one is present in all stages of the previous ones. Furthermore, we depicted how technology is present throughout the co-creation process and in each dimension specifically. In conclusion, this model expands the basis of co-creation in the curriculum literature and provides tools for practitioners to innovate in their academic contexts and involve students in their own learning process through co-creation. Further research in this field should be carried out, so we intend to apply this research to other fields of study and educational levels, contexts, and situations.

ICT integration in FLT: An analysis of TPACK implementation in Spanish Primary Teacher Education

Tania F. Gómez Sánchez — 2024-07-01

This study explores primary teachers´ initial training programs, focusing on Foreign Language Teaching (FLT) and its integration with technology. The research is grounded in two dimensions of contemporary society: plurilingual competence and digital literacy. The study employs the conceptual framework of "Technological Pedagogical Content Knowledge" (TPACK) (Mishra & Kohler, 2006) and applies content analysis methodology. The scientific interest lies in the scarcity of studies examining this specific area within the Spanish context, because research on TPACK in FLT has primarily focused on Asia and the Middle East. To address this void, a comprehensive national study encompassing 39 public universities was conducted. This study involved an in-depth analysis of 496 course guides within the field of FLT in primary education teacher training programs. The research findings indicate that less than half of the subjects incorporate technology, and when they do, two prominent trends emerge: the integration of TPACK and the presentation of technology as a broad competency, not specifically tailored to FLT. The primary conclusion drawn from this study is that the incorporation of TPACK in this context is moderate, emphasizing the need for a more comprehensive integration of technology within FLT teacher training programs.

Foreign Language Teacher's Attitudes Towards a Pre-designed Language Learning System

Roxana Rebolledo — 2024-07-01

Once the pandemic concluded, the Foreign Languages Department of a Chilean state university hired a Canadian company to implement a pre-designed language learning system (PLLS). This platform was to be used by all teachers and students, as it contained various activities to develop all four language skills, including pronunciation practice through AI-based voice recognition. This study explores the attitudes of 17 university teachers towards using these pre-elaborated resources, activities, and assessments in their communicative English and German courses. A mixed-method approach was used, involving a survey based on the Technology Adoption Model (TAM) and individual interviews. Descriptive statistics were obtained from the survey responses, and qualitative data were analysed using content analysis techniques.

The results indicate that teachers' attitudes towards the PLLS were generally neutral to negative. Instructors expressed their concerns about the system's pre-designed content and perceived functionality. Perceived ease of use and usefulness were rated low, reporting difficulties in navigation and alignment with their teaching styles. Perceived enjoyment received the lowest rating, mentioning issues such as disconnected content and lack of progressive structure. Qualitative data revealed technical problems, increased workload, and concerns about the system's impact on student motivation and learning outcomes. While some positive aspects were noted, the overall attitude towards the PLLS was predominantly negative, highlighting the need for better alignment with pedagogical goals and improved implementation strategies.