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Revista de Pedagogie Digitala

Artificial Intelligence and Student Academic Development: Use, Perceptions and Concerns Among Final Year Students in the Department of Development Studies, Midlands State University, Zimbabwe

• Cephas Mandirahwe, Tapiwa Patson Sisimayi

The rapid uptake of Artificial Intelligence (AI) within higher education in Africa represents a significant technological shift with implications for teaching, learning and student academic development. This study examined how undergraduate students use AI tools and how they perceive the effects of AI on their academic development. A mixed-methods design was employed at a selected public university in Zimbabwe, combining a cross-sectional student survey administered through the KoboToolbox (69 valid responses) with qualitative input from in-depth interviews and observation. The findings show near-universal awareness of AI, with use led by general-purpose tools (ChatGPT, 59.4 percent) and access dominated by personal laptops (85.5 percent). Students used AI mainly to understand difficult concepts and generally rated it at least moderately effective for their academic development, while also voicing substantial concerns about the accuracy of AI-generated information, over-reliance and the weakening of critical-thinking skills, the cost of advanced tools, and academic integrity. The most commonly reported negative consequence was reduced effort in personal research. The study advocates institutional action beyond mere technology adoption and recommends a clear, ethical AI policy and continuous staff professional development to support the responsible use of AI. The study extends a recent qualitative case study on the same university by Gawe & Gudyanga (2025) by adding survey-based evidence on patterns of use, access, cost and self-reported negative consequences. As a small, single-institution, cross-sectional and descriptive study, it does not establish causal or statistically significant associations between AI use and psychological outcomes such as stress or anxiety.

Articol integral: Artificial Intelligence and Student Academic Development: Use, Perceptions and Concerns Among Final Year Students in the Department of Development Studies, Midlands State University, Zimbabwe

Socofagia: The Algorithmic Smoothing of Cognitive Effort and a Proposal for ARN Digital as Counter-Practice

• Antonio Carlos González-López

The rapid, large-scale adoption of generative artificial intelligence is shifting human memory towards external systems of cognitive control. Presented as a conceptual and exploratory contribution within the socio-critical paradigm, with a qualitative interpretation of results, this study analyses twenty-five cases gathered through a six-item open questionnaire on technology use, externalisation of the self, decision-making autonomy, identity and relational bonds. The article introduces the concept of socofagia, in dialogue with Byung-Chul Han’s critique of the burnout society, to name the algorithmic smoothing of cognitive effort. It then proposes ARN Digital (a Spanish acronym for “Necessary Real Attitude towards the Digital”) as a preliminary, theory-driven practice of deliberate dosing of technology use, organised in three operational phases (detection, intervention and follow-up) and articulated through Bloom’s taxonomy and Miller’s pyramid. The article reports the diagnostic phase of an action-research programme; the counter-practice has not yet been implemented or evaluated. The findings reveal a productive tension. Informants report a strong sense of continuity in their identity, yet they describe a decision-making autonomy increasingly entangled with external systems, and a shift of relational bonds towards the machine when human attention is perceived as scarce.

Articol integral: Socofagia: The Algorithmic Smoothing of Cognitive Effort and a Proposal for ARN Digital as Counter-Practice

Digital Natives, Analogue Pedagogy? Teacher-Student Dynamics Across the Generation Z Divide in Romanian Secondary Education

• Maria-Mădălina Balea

Generation Z students bring digital fluency, shortened attention rhythms, and a preference for experiential learning into classrooms still shaped by pre-digital pedagogy. This mixed-methods study examines how 100 Romanian secondary-school teachers perceive and respond to the generational characteristics of their students, complemented by focus-group interviews with 10 middle- and high-school students. Results reveal a pronounced awareness–practice gap: while 85% of teachers report familiarity with Generation Z traits and 88% acknowledge the need for pedagogical adaptation, only 44% successfully diversify their methods to the point where difficulties diminish. Students, in turn, describe teaching as insufficiently responsive to their learning preferences. The study identifies attention maintenance, student disengagement, and disciplinary tensions as the dominant challenges, and shows that teachers who employ blended, interactive, and technology-enhanced strategies report significantly fewer classroom difficulties. These findings carry practical implications for teacher professional development in digitally evolving educational contexts.

Articol integral: Digital Natives, Analogue Pedagogy? Teacher-Student Dynamics Across the Generation Z Divide in Romanian Secondary Education

Developing Future Teachers’ Self-Efficacy in Digital Learning Environments: The Case of Kazakhstan

• Meiramgul Kuttybayeva, Miray Doğan

This study examines how prospective teachers in Kazakhstan develop self-efficacy for teaching in digital learning environments and identifies the individual, organizational, and systemic mechanisms that facilitate or impede this process. It integrates international research on teacher self-efficacy, established digital competence frameworks such as TPACK and DigCompEdu, and current developments in Kazakhstan’s educational policies and technological infrastructure. The paper explores how personal beliefs about teaching capabilities, prior pedagogical experiences, and institutional contexts shape prospective teachers’ confidence in integrating technology into instruction. It further analyses the factors that strengthen digital self-efficacy, highlights the critical role of institutional support in cultivating sustained competence, and addresses the implications of the urban–rural digital divide for equity in teacher preparation. The study concludes with recommendations for teacher education programs to establish a sustainable model for developing digital self-efficacy among future teachers in Kazakhstan.

Articol integral: Developing Future Teachers’ Self-Efficacy in Digital Learning Environments: The Case of Kazakhstan

Algorithmic Mediation, Learner Agency, and Cognitive Autonomy in AI-Enhanced Online Learning Environments

• Cristina-Georgiana Voicu

This article examines the psychological and behavioural implications of artificial intelligence integration in online learning environments, focusing on how algorithmic personalization, predictive feedback, and adaptive sequencing influence learner agency, cognitive autonomy, and self-regulation. Drawing on self-determination theory, cognitive psychology, and behavioural science, the study highlights both the supportive and constraining effects of AI-mediated learning. While adaptive systems can enhance perceived competence, reduce cognitive load, and support task alignment, they may also introduce subtle behavioural steering mechanisms that externalize regulation and diminish intrinsic motivation. The analysis shows that algorithmic nudging can recalibrate learners’ perceptions of control and responsibility, normalizing compliance with system-defined pathways. To address these tensions, the article proposes a psychologically grounded framework for ethically aligned AI-enhanced learning that balances adaptive scaffolding with reflective choice and exploratory engagement. By clarifying the cognitive and motivational mechanisms through which algorithmic systems reshape learner agency, the study offers design principles for autonomy-supportive AI-mediated learning environments.

Articol integral: Algorithmic Mediation, Learner Agency, and Cognitive Autonomy in AI-Enhanced Online Learning Environments

Artificial Intelligence: A Maturity Test. Perspectives on Learning, Teaching, and Assessment

• Olimpius Istrate, Stefania Capogna, Oana Barbu-Kleitsch, François Jourde

The integration of generative artificial intelligence into education is reshaping the processes of learning, teaching, and assessment. This article analyses the implications of this transformation from four complementary perspectives: (1) the reflexive character of AI as a “mirror” of human thought and the cognitive maturity test it imposes; (2) the restructuring of cognitive processes and the risks of diminished metacognitive engagement; (3) the redefinition of human-specific competences in relation to AI capabilities; and (4) the need for human-centred curriculum design and assessment redesign to support authentic learning. Drawing on recent specialised literature and OECD reports (2025, 2026), the analysis reveals a central tension between the potential for learning personalisation at scale and the risk of the “mirage of false mastery” – a phenomenon whereby AI-generated outputs mask the underdevelopment of fundamental competences. The article argues for “pedagogical intentionality” – a deliberate reorientation from AI-driven products toward human-centred processes, prioritising the development of transversal, socio-emotional, and metacognitive competences as a response to the challenges and opportunities of AI in education.

Articol integral: Artificial Intelligence: A Maturity Test. Perspectives on Learning, Teaching, and Assessment

Reclaiming Humanistic Agency in the Age of Algorithms: Toward a Posthuman Pedagogy of the Humanities

• Cristina-Georgiana Voicu

Within the context of accelerating digital transformation, the emergence of generative artificial intelligence (AI) has redefined the epistemic and ethical foundations of the humanities. The algorithmic turn challenges the traditional role of humanistic inquiry, raising questions about interpretation, creativity, and meaning in a technologically mediated world. This article explores how posthuman pedagogy can reclaim humanistic agency in the age of algorithms. Drawing on theoretical frameworks from posthumanism (Braidotti, Haraway) and metamodernism (Vermeulen & van den Akker), it argues that AI does not signal the decline of the humanities but their evolution toward a relational and ethically responsive practice. The study identifies three interrelated competencies – algorithmic literacy, digital empathy, and critical co-agency – as essential pillars for a transformative humanities curriculum. These competencies enable learners to engage critically and ethically with intelligent systems, interpret algorithmic processes as cultural texts, and act responsibly within distributed cognitive environments. Beyond its theoretical contribution, the article also addresses significant ethical and socio-cultural concerns, including algorithmic bias, epistemic injustice, and the need for reflexive digital ethics in higher education. It advocates for a metamodern orientation that balances skepticism with hope and critique with reconstruction. The conclusion emphasizes that the humanities must not resist technological mediation but reinterpret it as an opportunity for ethical imagination. Posthuman pedagogy thus envisions education as a co-creative process between human and algorithmic intelligences, grounded in empathy, reflection, and moral responsibility.

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Educational Decision-Making in Digital Education: A Conceptual Review of Data-Driven, Data-Based, and Data-Informed Approaches

• Evelina Brazauskienė

Theoretical differences between data-driven decision-making (DDDM), data-based decision-making (DBDM), and data-informed decision-making (DIDM) approaches have received relatively limited attention in digital pedagogical environments. This conceptual review draws on peer-reviewed literature between 2009 and 2025 to clarify these differences and examine their pedagogical implications. While DDDM is often reliant on systematic data use and predictive tools, DBDM is concerned with collaborative interpretation supported by digital dashboards and formalized methodologies, and DIDM integrates professional judgment with digital evidence and ethical considerations. The analysis highlights the impact of digital environments – such as learning management systems, digital trace data, and new AI-supported tools – on educational decision-making. Each approach has distinct benefits and challenges that have implications for teacher professional development and learning as well as institutional practices. An understanding of these differences is essential to effectively balance technological capabilities with pedagogical expertise, as well as to foster ethical and context-aware data use in contemporary education.

Articol integral: Educational Decision-Making in Digital Education: A Conceptual Review of Data-Driven, Data-Based, and Data-Informed Approaches

Artificial Intelligence for Educators – Practical Guidelines: Tool Selection, Attribution, and Assessment of Student Work

• Olimpius Istrate

The observation that artificial intelligence plays and will continue to play a prominent role across all professional fields, in political and social life, in education, and for personal development has led to growing awareness of the importance of making anticipatory adjustments to educational systems and processes. This recognition has prompted the proposal and continuous refinement of various resources: suggestions, guidelines, reference frameworks, educational policy documents, and legislative regulations that vary in their utility, pertinence, and coherence, yet remain undeniably relevant for our changing times.
Building upon these existing resources, this article serves as a practical introductory guide for the responsible integration of artificial intelligence in teaching and research activities. It provides useful elements for selecting AI tools appropriate to specific pedagogical tasks, reviews protocols for citing and acknowledging AI contributions in various professional contexts, and proposes effective methods for assessing the authenticity of student work in the AI era. The guide advocates for maintaining a careful balance between harnessing technological potential and preserving the essential human component in the educational process.

Articol integral: Artificial Intelligence for Educators – Practical Guidelines: Tool Selection, Attribution, and Assessment of Student Work

Percepții și practici ale cadrelor didactice privind integrarea inteligenței artificiale în educație: un studiu transnațional în România, India, China și Brunei

• Carmen Cioranu-Rădulescu, Sneh Bansal, Yuanting Liao, Mursidi Murah

Teachers’ perceptions and practices regarding the integration of artificial intelligence in education: a transnational study in Romania, India, China and Brunei

This research examines the transformative role of artificial intelligence (AI) in education, placing it within the broader context of a cognitive industrial revolution. Despite the increasing integration of AI-based tools – such as automated assessment systems, adaptive learning platforms or virtual assistants – their adoption in education remains uneven globally. This disparity, driven by institutional, cultural or infrastructural differences, risks deepening existing educational inequalities and fostering superficial use of digital technologies. The present study draws on empirical data collected in July 2024 from over 250 teachers in Romania, India, China and Brunei, to investigate perceptions of the effectiveness, frequency of use and integration of AI tools in teaching practice. Variables such as prior professional training, teaching experience, internet access and field of study are analyzed. Through comparative and contextualized analysis, the research highlights the need for adapted training programs, informed educational policies, and culturally sensitive pedagogical innovations. The results contribute to filling a significant gap in the literature, which has thus far neglected the transnational empirical perspective on how teachers evaluate and use educational technologies based on artificial intelligence.

Articol integral: Percepții și practici ale cadrelor didactice privind integrarea inteligenței artificiale în educație: un studiu transnațional în România, India, China și Brunei