EthAIca (Journal)
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Platform for learning programming and databases based on artificial intelligence
Get PDFThis final degree project proposed the development of a gamified web platform to facilitate the initial learning of programming and databases using artificial intelligence. The proposal arose from the need for new teaching tools given the difficulties presented by traditional teaching methods. The objective was to create an application that teaches basic concepts in an interactive and entertaining way. To do this, an investigation was carried out to determine the main contents to be addressed. Then theoretical contents were defined and practical exercises were designed applying gamification techniques. Subsequently, a functional prototype was developed that contains the defined theoretical contents, implements the designed practical exercises, and integrates the artificial intelligence functionality to provide unlimited examples on each topic, correction and personalized feedback on the resolution of exercises performed by the student. The results obtained so far allow validating the usefulness and technical feasibility of the proposal
Gender, age, and emotion-aware strategies in AI-enhanced education: insights from future educators and algorithmic thinking in primary schools
Get PDFIntroduction: Artificial Intelligence (AI) is rapidly transforming educational landscapes. Understanding how educators and students perceive and engage with AI is crucial for effective integration.Objectives: This study aims to (1) analyze the attitudes of future educators toward AI in teaching, considering variables such as gender and age, and (2) evaluate the effectiveness of emotion-aware, ICT-based instructional strategies in enhancing algorithmic thinking among primary school pupils.Methods: A mixed-methods approach was employed. Quantitative data on pre-service teachers’ perceptions were collected via surveys from participants at state-managed universities in the Zamboanga Peninsula, Philippines. Additionally, an experimental pedagogical intervention using emotion-sensitive strategies was implemented in selected primary schools to assess changes in students\u27 algorithmic thinking skills.Results: Statistical analyses revealed significant differences in AI-related perceptions based on gender and age among pre-service teachers. Furthermore, primary school pupils who participated in the emotion-aware instructional activities showed notable improvements in algorithmic thinking competencies compared to control groups.Conclusions: The findings underscore the importance of aligning AI integration with the emotional and sociocultural dynamics of both teachers and learners. Emotion-sensitive strategies not only foster computational competencies in young students but also create inclusive teaching environments. The study advocates for thoughtful, context-aware implementation of AI in education to maximize its transformative potential
Human-in-the-Loop Models for Ethical AI Grading: Combining AI Speed with Human Ethical Oversight
Get PDFThe adoption of AI-powered grading systems in academic institutions promised improved efficiency, consistency, and scalability. However, these benefits introduced ethical challenges, including algorithmic bias, contextual insensitivity, and reduced transparency, particularly in high-stakes assessments. To address these concerns, the chapter presented a Human-in-the-Loop (HITL) grading framework that integrated AI-generated recommendations with human oversight. The model consisted of four layers: (i) pre-grading configuration with customizable rubrics and model calibration; (ii) preliminary scoring using transformer-based language models; (iii) human validation and contextual adjustment of AI outputs; and (iv) transparent feedback supported by dual-logged audit trails. A case study was conducted at a mid-sized university, where the framework was applied to 800 undergraduate essays. As a result of this implementation, the faculty validated 87 % of the AI-generated scores with only minor adjustments, while 13 % required overrides due to misinterpretations involving creative expression, linguistic nuance, or cultural context. The grading time was reduced by 40 %, and student satisfaction improved due to transparent assessment and educator involvement. These findings demonstrate that the HITL model has the potential to balance automation with ethical oversight, promoting fairer evaluations and preserving academic integrity. It enhanced faculty agency, ensured equity across diverse student populations, and built trust through explainable AI tools such as SHAP and LIME. The chapter concluded by proposing policy guidelines, technical integrations, and communication strategies, while advocating for future applications in multimodal grading and open-source ethical assessment platforms
The Role of ChatGPT in Academic Writing: Pedagogical and Ethical Dimensions
Get PDFIntroduction: Generative AI tools such as ChatGPT are reshaping academic writing in higher education, offering both opportunities for linguistic support and creativity, while raising concerns over authorship, plagiarism, and academic integrity.
Objective: This study examines the pedagogical benefits and ethical challenges of ChatGPT in academic writing, exploring how it can be integrated responsibly into higher education practices.
Methods: A qualitative thematic synthesis of 33 peer-reviewed studies, reports, and theoretical essays published between 2022 and 2025 was conducted. The analysis focused on two axes: pedagogical applications in writing instruction and ethical implications for academic integrity and authorship.
Development: Findings indicate that ChatGPT can serve as a valuable writing coach, enhancing brainstorming, drafting, and revision processes, particularly for multilingual and novice writers. However, issues of algorithmic dependence, fabricated content, plagiarism risks, and unequal access remain significant. The study concludes that effective use of ChatGPT requires AI literacy, transparent disclosure, and equitable institutional policies. A balanced integration of AI, supported by critical pedagogy, can empower students while safeguarding academic standards
Thinking about artificial intelligence from an ethical, critical and socially committed point of view
Get PDFArtificial intelligence has redefined technology and its implications across different levels of society, accelerating the pace of information dissemination. This gives rise to two dimensions: the first refers to the (lack of) control over the flow of information, shaped by specific responses that generative technologies offer to users in a contextualized and supposedly reliable manner; the second concerns the sense of technological omnipresence imposed on the user. All of this stems from a development that has prioritized the technical over the ethical component. Therefore, we present EthAIca: Journal of Ethics, AI and Critical Analysis, offering a critical and interdisciplinary perspective that addresses and makes visible the system’s asymmetries and promotes socially committed and global solutions
Attitudes and perceptions toward artificial intelligence on teacher job satisfaction at a medical school in northern Peru
Get PDFObjective: determine the relationship between attitude and perception of AI in teaching job satisfaction at a Faculty of Human Medicine. Materials and methods: A quantitative, non-experimental, analytical-correlational and transectional research was carried out, with a sample of 87 teachers selected through non-probabilistic sampling. Results: The results revealed that 74.7% of teachers expressed positive attitudes towards AI, while 80.5% presented positive perceptions. Regarding job satisfaction, 78.2% reported a regular level, 20.7% a high level and only 1.1% a low level. Perception towards AI showed a low but significant positive correlation with job satisfaction (Rho = 0.285, p = 0.036), while attitudes did not show a significant relationship (p = 0.264). Additionally, it was found that factors such as the contractual employment relationship influence openness towards AI. Hired teachers with less experience (1-3 years) showed a greater positive predisposition towards technology. Conclusions: It was determined that the perception towards AI of university teachers has a significant relationship with their job satisfaction. These findings underscore the importance of teacher training and institutional policies to integrate AI effectively, optimizing both job satisfaction and educational performance
Algorithmic Bias and Data Justice: ethical challenges in Artificial Intelligence Systems
Get PDFThis article examines the critical ethical challenges posed by algorithmic bias in artificial intelligence (AI) systems, focusing on its implications for social justice and data equity. Through a systematic review of case studies and theoretical frameworks, we analyze how biased datasets and algorithmic designs perpetuate structural inequalities, particularly affecting marginalized communities. The study highlights key examples, such as gender and racial biases in facial recognition and hiring algorithms, while exploring mitigation strategies rooted in data justice principles. Additionally, we evaluate regulatory responses, including the European Union\u27s AI Act, which proposes a risk-based governance framework. The findings underscore the urgent need for interdisciplinary approaches to develop fairer AI systems that align with ethical standards and human rights
Perceptions of AI Collaboration in Writing among Teacher Aspirants: An Empirical Cross-Sectional Study among Teacher Aspirants
Get PDFThe integration of artificial intelligence (AI) into education has generated increasing interest, particularly in its role in academic writing. While prior studies have examined students’ use of AI, limited attention has been given to teacher aspirants’ perceptions of AI collaboration with human writers across subject disciplines. Addressing this gap is crucial in preparing future educators for responsible AI integration in teaching and learning. This study aimed to determine the perceptions of English, science, and mathematics teacher aspirants toward AI collaboration with human writers in academic essay writing and to examine differences across subject disciplines. A descriptive‒quantitative design was employed, involving 90 undergraduate teacher aspirants equally distributed across the three disciplines. Stratified random sampling was used to ensure adequate representation, and data were collected through a structured questionnaire consisting of 10 items on a 5-point Likert scale with high internal reliability (α = 0,94). The data were analyzed via descriptive statistics and one-way ANOVA. The findings revealed generally positive perceptions of AI’s role in writing, particularly in generating outlines, assisting with citations, and supporting editing processes. Significant differences emerged among disciplines, with science majors expressing the most favorable perceptions (M = 4,13), followed by English (M = 3,94) and mathematics majors (M = 3,90). The study concludes that disciplinary orientation shapes openness to AI collaboration in academic writing. It is recommended that teacher education programs integrate structured training on the ethical and effective use of AI, ensuring a balance between technological assistance and the preservation of creativity and critical thinking
A dignitarian approach to ai ethics: grounding normative principles in human value
Get PDFIntroduction: The proliferation of guidelines for artificial intelligence ethics presented a field without a firm philosophical foundation. Current documents offered a disparate collection of principles, often lacking a unified justification for their normative force. This paper confronted that deficiency by proposing a novel dignitarian framework. The objective of this research was to establish a stable and rationally defensible basis for the design, deployment, and governance of AI systems.Methods: This study employed a conceptual analysis of the Kantian philosophical tradition to define human dignity as an absolute, intrinsic value. This core concept was then formalized into a coherent axiomatic system using elementary set theory and deontic logic. The analysis was based on a critical review of foundational texts in moral philosophy and contemporary AI ethics literature.Results: A primary normative constraint emerged from this formalization: an AI system\u27s action, a, was morally permissible only if it did not treat any person, p, merely as a means to an end. This was expressed logically as Permissible(a) → ∀p ∈ P, ¬ViolatesDignity(a, p). This principle functioned as a strict deontological limit on any goal-oriented programming.Conclusions: The proposed framework provided a stable and rationally defensible basis for the design, deployment, and governance of AI systems. It moved the conversation from a list of suggestions to a structured ethical system, contributing to the growing field of computational ethics by offering a clear, implementable, and non-negotiable constraint on AI behavior
Exploring Academic Librarians’ Perception towards Artificial Intelligence in Nigerian Polytechnics
Get PDFIntroduction: Artificial intelligence is increasingly shaping library practices worldwide. Although Nigerian academic libraries are gradually embracing digital technologies, little is known about how librarians in polytechnic institutions interpret the integration of artificial intelligence in their work environment.Objective: The study aimed to examine the perceptions of academic librarians in Nigerian polytechnics regarding the adoption of artificial intelligence in library operations.Method: A survey design using mixed methods was employed. Quantitative data were collected from fifty academic librarians, while qualitative insights were obtained from five heads of ICT or automation units. Participants were purposefully selected from five polytechnic libraries in the South South region of Nigeria. Descriptive statistics and narrative analysis were used to analyse the data.Results: The study shows that librarians are aware of artificial intelligence and acknowledge its value in improving library services. However, concerns about job security and institutional readiness influence their attitudes toward adoption. While respondents recognise the potential of artificial intelligence to enhance user satisfaction and operational efficiency, they also highlight the need for adequate training and supportive infrastructure.Conclusion: The perceptions of librarians reflect both enthusiasm and caution toward artificial intelligence adoption. To ensure meaningful integration, institutions must invest in capacity development, strategic planning, and supportive policies. Strengthening the digital competence of librarians will be essential for sustaining their relevance and ensuring effective participation in emerging technological landscapes