Conference Agenda
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16 SES 10 B
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16. ICT in Education and Training
Paper Digital Pedagogical Intentionality and Design Thinking in Initial Teacher Education: Teaching Profiles and Levels of Digital Technology Integration 1: Universidad de La Frontera, Chile; 2: Universitat Rovira i Virgili, Spain Presenting Author:Over the last decade, and with intensity following the transition to emergency remote teaching, the use of digital technologies in higher education has expanded significantly (Syahrin et al., 2023; Tang, 2022). This scenario has increased research interest in the field; however, available evidence shows that a large share of this academic production remains focused on access to resources and technical mastery of technologies, reinforcing a predominantly instrumental orientation of professional digital competence, to the detriment of approaches that critically and reflectively address its pedagogical and epistemological implications (Aagaard et al., 2025). In this context, various studies warn that the educational effectiveness of digital technologies does not depend on their mere availability or frequency of use, but rather on how teachers mobilize pedagogical skills to integrate them into the design of active learning activities and on the degree of participation assumed by students in these processes (Lohr et al., 2024). Nevertheless, a gap persists in the literature, characterized by descriptions of technological advances without sufficient analysis of the pedagogical principles that guide their use toward high-quality learning, which limits understanding of how these tools effectively contribute to the teaching–learning process (Almithqal & John, 2024; Ansari & Waheed, 2024). Within this scenario, design thinking emerges as a critical framework for understanding educational innovation. It is defined as an analytical and creative process that enables experimentation, prototyping, and redesigning solutions to complex problems (Razzouk & Shute, 2012). Its relevance is such that Tsai and Chai (2012), expanding on Ertmer’s (1999) original proposal, position it as a third-order barrier. From this perspective, design thinking functions as an approach that enables teachers to reinterpret and negotiate infrastructural constraints and professional beliefs within specific contexts, rather than addressing them as isolated barriers. This perspective helps explain why, even under similar institutional conditions, profoundly different pedagogical practices emerge (Blundell, 2025). Alongside this design capacity, digital pedagogical intentionality plays a decisive role. It is understood as the deliberate orientation that guides decisions regarding instructional design, defining the educational purposes that structure the use of methods and resources. However, there is a scarcity of studies that explicitly articulate teachers’ digital pedagogical intentionality with design thinking. This absence hinders understanding of the mechanisms that enable the transformation of the learning experience rather than the mere reproduction of traditional models. Addressing this gap is critical in initial teacher education, where university practices shape future school teaching. Based on the above, the purpose of this study was to analyse the relationship between three forms of digital pedagogical intentionality (teaching-focused, learning-focused, and didactic modelling-focused) and three levels of design thinking (initial, intermediate, and advanced) among academics involved in initial teacher education. Methodology, Methods, Research Instruments or Sources Used The study adopted an interpretive qualitative approach, aimed at understanding the meanings participants attribute to their experiences within a specific context (Merriam & Tisdell, 2015). This design involves data collection through interviews and inductive analysis oriented toward identifying patterns, categories, and emerging themes, prioritizing an in-depth understanding of the phenomenon. The study involved 54 academics (36 Chilean and 18 Spanish) from 10 universities (five in Chile and five in Spain) who use digital technologies in courses related to initial teacher education. Among Spanish academics, specialists in digital technologies predominate, whereas in the Chilean case, faculty members are characterized by using digital technologies primarily as a support resource in their teaching. This sample composition made it possible to capture a wide diversity of digital profiles. For data collection, a semi-structured interview guide was used, organized around five thematic dimensions: (i) professional trajectory; (ii) academic characteristics; (iii) conditions for implementing teaching; (iv) use of digital technologies in the classroom; and (v) experience with emergency remote teaching. Interviews were conducted both remotely and in person, reaching a total duration of 2,485 minutes, with an average of 43.5 minutes per session. Prior to participation, faculty members read and signed an informed consent form validated by the institutional ethics committee. After recording each interview, the information was transcribed using Microsoft 365 software, followed by manual review by two researchers. Subsequently, technical adjustments were applied to the transcripts to optimize AI-assisted analysis and incorporate the data into the MaxQDA software for organization and processing. Data analysis was conducted using principles from the structuring qualitative content analysis model proposed by Kuckartz and Rädiker (2023). In the first phase, deductive codes were established to identify digital pedagogical intentionality (with focuses on teaching, learning, and modelling of practices) and levels of design thinking with technologies (initial, intermediate, and advanced). In the subsequent stage, MaxQDA’s AI chat was used as an analytical support tool to classify teachers and explore regularities, contrasts, and distinctive elements among profiles. AI use was employed as a complementary resource under researcher supervision. All system-generated responses were validated through review of the hyperlinks provided by the system. The construction of conclusions and the final interpretation of the study were developed by the research team. Conclusions, Expected Outcomes or Findings The results revealed six teaching profiles, structured according to the combination of one dominant and one secondary pedagogical intentionality: Learning–Teaching (n = 22), Learning–Modeling (n = 8), Teaching–Learning (n = 12), Teaching–Modeling (n = 7), Modeling–Learning (n = 3), and Modeling–Teaching (n = 2). Data analysis showed that digital pedagogical intentionality prioritizing learning and didactic modelling mostly converge with advanced levels of design thinking. In contrast, teaching-centred orientations are predominantly associated with intermediate levels. These findings suggest that design thinking develops progressively as the emphasis of digital pedagogical intentionality shifts from teaching toward student learning. The findings indicate that the academic use of digital technologies transcends the limitations of restrictive institutional contexts. Resource availability does not directly determine digital pedagogical intentionality; instead, teacher agency—articulating intentional decision-making, self-directed learning, and creativity—constitutes a central explanatory factor in the transformative use of digital technologies. Didactic modelling intentionality acquires relevance in initial teacher education, as it positions technology as a second-order formative device that projects future professional practice and strengthens critical digital competencies with high transfer potential. Despite the diversity of profiles, a transversal core of design thinking is identified. This core integrates reflective attitude, pedagogical valuation of technology, self-directed learning, and peer learning. Taken together, the results demonstrate that the quality of pedagogical uses of digital technologies is best explained through a logic of intentional pedagogical design, rather than through approaches based on isolated digital competencies or external infrastructural conditions. This consolidates digital pedagogical intentionality as a key analytical construct. References Aagaard, T., Amdam, S. H., Nagel, I., Vika, K. S., Andreasen, J. K., Pedersen, C., & Røkenes, F. M. (2025). Teacher preparation for the digital age: Is it still an instrumental endeavor? Scandinavian Journal of Educational Research, 69(3), 651–665. https://doi.org/10.1080/00313831.2024.2330927 Almithqal, E. A., & John, T. (2024). Exploring barriers and facilitators of ICT in English pronunciation instruction: Perspectives from Jordanian tertiary education. Pedagogical Research, 9(4). https://doi.org/10.29333/pr/15028 Alvarado, L. F. (2025). Design thinking as an active teaching methodology in higher education: A systematic review. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1462938 Ansari, S., & Waheed, A. (2024). Investigating the barriers to sustainable higher education in the post pandemic environment. Education and Information Technologies, 29(18), 24677–24713. https://doi.org/10.1007/s10639-024-12728-6 Blundell, C. N. (2024). Using design thinking to embrace the complexities of teacher learning-practice with digital technologies. Professional Development in Education, 51(3), 386–404. https://doi.org/10.1080/19415257.2024.2422063 Ertmer, P. A. (1999). Addressing first- and second-order barriers to change: Strategies for technology integration. Educational Technology Research and Development, 47(4), 47–61. https://doi.org/10.1007/BF02299597 Kuckartz, U., & Rädiker, S. (2023). Qualitative content analysis: Methods, practice and software (Second. ed.). SAGE Publications. Lohr, A., Sailer, M., Stadler, M., & Fischer, F. (2024). Digital learning in schools: Which skills do teachers need, and who should bring their own devices? Teaching and Teacher Education, 152. https://doi.org/10.1016/j.tate.2024.104788 Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and implementation. Jossey-Bass. Razzouk, R., & Shute, V. (2012). What is design thinking and why is it important? Review of Educational Research, 82(3), 330–348. https://doi.org/10.3102/0034654312459091 Syahrin, S., Almashiki, K., & Alzaanin, E. (2023). The impact of COVID-19 on digital competence. International Journal of Advanced Computer Science and Applications, 14(1). https://doi.org/10.14569/ijacsa.2023.0140156 Tang, K. H. D. (2022). Impacts of COVID-19 on primary, secondary and tertiary education: A comprehensive review and recommendations for educational practices. Educational Research for Policy and Practice, 22(1), 23–61. https://doi.org/10.1007/s10671-022-09319-y Tsai, C.-C., & Chai, C. (2012). The "third"-order barrier for technology-integration instruction: Implications for teacher education. Australasian Journal of Educational Technology, 28(6), 1057–1060. https://doi.org/10.14742/ajet.810 16. ICT in Education and Training
Paper Exploring student views on using Student Response Systems for real-time Feedback in Classes University of Prishtina, Kosovo Presenting Author:Background The growing use of tools like Kahoot!, Mentimeter, and Padlet has fostered greater participation and real-time feedback, which enhances student engagement and promotes interest in theoretical concepts (Kloos et al., 2022). SRS are recognized for their pedagogical benefits, as they align with several educational theories, including Kolb’s Experiential Learning Theory, Constructivism, Cognitive Multimedia Learning, Just-in-Time Teaching, and Game-Based Learning. These theories support active student engagement and motivation (Kolb et al., 2014; Chaiyo & Nokham, 2017). Kolb’s model, for instance, emphasizes the interplay between perception and processing, where learning emerges from students' concrete experiences and reflective observations. Studies investigating Student Response Systems highlight key factors influencing their adoption, such as ease of use, usefulness, and social influence. Research on tools like Padlet has shown that these factors positively influence tool acceptance among students. Similarly, tools such as Mentimeter, Wooclap, Microsoft whiteboard, and Miro have been explored for their ability to enhance learning orchestration and facilitate collaboration among students (Kloos et al., 2022; Avila & Castillo, 2021; Juhary, 2021; Karsen et al., 2022). Research highlights the positive impact of SRS on student outcomes, including improved motivation, retention of content, and critical thinking skills (Chien et al., 2016; Roschelle et al., 2004). The adoption of digital and web-based systems has further expanded the capabilities of SRS, allowing integration with mobile devices, laptops, and other platforms. This evolution has made SRS accessible and scalable for a wide range of learning environments, from large lecture halls to small group discussions (Beatty, 2004). However, despite the benefits, challenges such as technical difficulties and internet connectivity issues, as well as teachers' limited pedagogical expertise, have been identified as barriers to the effective integration of these tools in classrooms (Qurbani, 2022).
Aim and Research Questions The aim of this research paper is to explore the integration of Student Response Systems (SRS) into classroom settings, focusing on how these tools enhance the teaching and learning experience. This study examines the practical implementation of SRS in real-life classroom scenarios, analyzing their effectiveness in fostering student engagement, participation, and interaction. Additionally, it investigates the extent to which the use of SRS impacts class dynamics. By evaluating both the benefits and challenges associated with SRS, this research seeks to provide actionable insights into their role in transforming traditional teaching methods into more interactive and student-centered learning environments. The research is driven by the following research questions: RQ1: What are students' perspectives on the use of Student Response Systems (SRS) in classroom settings? RQ2: What specific Student Response Systems (SRS) are currently available for facilitating real-time feedback in classroom settings? RQ3: What is the overall sentiment of students toward the integration of SRS in their learning experience?
Methodology, Methods, Research Instruments or Sources Used A qualitative research methodology was employed to address the research questions, using techniques such as focus groups and sentiment analysis of students' opinions. These methods provided in-depth insights into students’ experiences and practical perspectives on the use of Student Response Systems (SRS) in classroom settings. Data were collected by gathering input from 103 students from the Faculty of Education during the winter semester of 2024. The students were divided into four focus groups, each designed to encourage open dialogue and rich discussion about their experiences with Students Response Systems. These tools included popular platforms like Kahoot, Slido, Plickers, Padlet, and Mentimeter – to name a few, which are commonly used for real-time student feedback in educational settings. The focus group discussions explored various dimensions of SRS integration in the classroom. Participants shared their perspectives on the benefits of these systems, such as increased engagement, improved interactivity, and opportunities for immediate feedback. They also discussed the challenges they encountered, including technical issues, accessibility concerns, and potential overuse of such systems. Open-ended questions encouraged students to reflect on their familiarity with specific SRS platforms, their perceptions of ease of use, and the practicality of implementing these tools in diverse educational contexts. In addition to the qualitative insights gathered from focus groups, sentiment analysis was employed to assess the tone and emotional responses reflected in students’ opinions. Using Natural Language Processing (NLP) and Machine Learning techniques, the focus group transcripts were analyzed to identify positive, negative, and neutral sentiments (Kastrati et al., 2021). This analysis provided a deeper understanding of students’ emotional reactions to SRS, revealing patterns in their attitudes toward the technology. For example, positive sentiments often highlighted the fun and interactive aspects of SRS, while negative sentiments pointed to frustrations with technical glitches or limited applicability in certain subjects. The combination of focus groups discussions and sentiment analysis offers a comprehensive approach to understanding the integration of SRS in classroom settings. While the focus groups captured nuanced, qualitative insights directly from students, sentiment analysis added an additional layer of data by quantifying and categorizing sentiment of students responses. Together, these methods provide a holistic view of how SRS tools are perceived by students, the benefits they bring, and the challenges that need to be addressed to maximize their effectiveness in educational environments. Conclusions, Expected Outcomes or Findings This paper explores students' opinions on the use of Student Response Systems (SRS) to enhance classroom dynamics through real-time feedback. Tools such as Kahoot!, Slido, Plicker, Padlet, and Mentimeter have transformed classroom environments by promoting active participation, addressing misconceptions, and enabling adaptive teaching strategies. These platforms facilitate anonymous input, cater to diverse learning styles, and create more engaging learning experiences. The study collected qualitative data from 103 students in the Faculty of Education, examining their perceptions, preferences, and usage patterns of these SRS tools. The findings provide substantial insights into students' preferences regarding Student Response Systems, their usage patterns, and the preferred methods for delivering feedback. Students response systems such as Kahoot!, Socrative, Mentimeter, Plickers, Wooclap, Padlet, Edpuzzle, Slido, and Microsoft and Google Forms emerged as significant examples in this context. Notably, a considerable proportion of students expressed a preference for providing feedback using platforms like Kahoot!, Padlet, and Plickers, underscoring the importance of anonymity, privacy and gamification features in the feedback process. Furthermore, the shared opinions offered a nuanced understanding of how these tools impacted student experiences in classroom engagment, and how the SRS tools contribute to the overall learning experience in in classrooms. The findings highlight the positive impact of SRS on student participation, classroom engagement, and learning outcomes, with particular emphasis on the benefits of anonymity and gamification features. Challenges in integrating these tools were emphasized, including technical difficulties, internet infrastructure, teacher and students' digital competencies, and variations in teachers' readiness to incorporate SRS effectively. In conclusion, the results provide critical insights into the feasibility of adopting SRS in contemporary educational settings. Despite the challenges, the findings suggest that SRS can significantly contribute to creating more interactive and responsive learning environments, ultimately enhancing student participation and learning outcomes. References Avila, S. R., & Castillo, E. V. (2021). Model to support the learning process and generation of knowledge using collaborative tools. In 2021 IEEE 1st International Conference on Advanced Learning Technologies on Education & Research (ICALTER) (pp. 1-4). IEEE. Caldwell, J. E. (2007). Clickers in the large classroom: Current research and best-practice tips. CBE—Life Sciences Education, 6(1), 9-20. Chaiyo, Y., & Nokham, R. (2017). The effect of Kahoot, Quizizz and Google Forms on the student's perception in the classrooms response system. In 2017 International conference on digital arts, media and technology (ICDAMT) (pp. 178-182). IEEE. Chien, Y. T., Chang, Y. H., & Chang, C. Y. (2016). Do we click in the right way? A meta-analytic review of clicker-integrated instruction. Educational Research Review, 17, 1-18. Juhary, J. (2021). Padlet for remote learning: Lessons learned. In 2021 Universitas Riau International Conference on Education Technology (URICET) (pp. 291-296). IEEE. Karsen, M., Pangestu, H., & Kristin, D. M. (2022). Acceptance of Miro and Padlet as Collaboration Tools on Hybrid Flipped Learning & Case-Based Learning in Education 4.0 (a case study approach). In 2022 International Conference on Information Management and Technology (ICIMTech) (pp. 577-582). IEEE. Kastrati, Z., Dalipi, F., Imran, A. S., Pireva Nuci, K., & Wani, M. A. (2021). Sentiment analysis of students’ feedback with NLP and deep learning: A systematic mapping study. Applied Sciences, 11(9), 3986. Kay, R. H., & LeSage, A. (2009). Examining the benefits and challenges of using audience response systems: A review of the literature. Computers & Education, 53(3), 819-827. Kloos, C. D., Fernández-Panadero, C., Alario-Hoyos, C., Moreno-Marcos, P. M., Ibáñez, M. B., Muñoz-Merino, P. J., ... & Estévez-Ayres, I. (2022). Programming Teaching Interaction. In 2022 IEEE Global Engineering Education Conference (EDUCON) (pp. 1965-1969). IEEE. Kolb, D. A., Boyatzis, R. E., & Mainemelis, C. (2014). Experiential learning theory: Previous research and new directions. In Perspectives on thinking, learning, and cognitive styles (pp. 227-247). Routledge. Nuci, K. P., Tahir, R., Wang, A. I., & Imran, A. S. (2021). Game-based digital quiz as a tool for improving students’ engagement and learning in online lectures. Ieee Access, 9, 91220-91234. Owen, H. E., & Licorish, S. A. (2020). Game-based student response system: The effectiveness of Kahoot! On junior and senior information science students’ learning. Journal of Information Technology Education: Research, 19, 511-553. 16. ICT in Education and Training
Paper Making Videogames Lendable: Designing Infrastructures to Advance Game-Based Pedagogy The University of Sydney, Australia Presenting Author:Digital games offer powerful opportunities for learning, meaning making, and engagement across educational contexts (Gee, 2003; Ehret et al., 2022). Narrative-driven and exploratory games, in particular, have been shown to support critical literacy, systems thinking, ethical reasoning, and identity development (Burn, 2021; Theodoulou & Curwood, 2023). Educational research is increasingly called upon not only to understand learning but also to intervene in the conditions that shape educational practice. The ECER 2026 theme, Knowing and Acting, foregrounds the dynamic relationship between research, institutional infrastructures, and pedagogical action, asking how educational research can respond to changing technological, cultural, and material conditions. This presentation addresses these concerns by examining a critical infrastructural gap that limits the educational use of digital games: the absence of scalable, sustainable models for libraries to purchase, license, and lend digital-only games to students. Unlike eBooks, films, or journals, games sit outside existing institutional procurement and distribution models, leaving educators to rely on ad hoc solutions that are costly, inequitable, and pedagogically limiting. This is a significant problem in secondary schools where games can support immersive and interactive learning as well as in higher education contexts where games are increasingly used in disciplines such as game design, digital humanities, media studies, and teacher education. Without a library-based solution, students may be excluded due to cost or platform restrictions, and educators have limited scope to leverage game-based pedagogy. These constraints undermine the educational potential of games and restrict their integration into formal curricula. As researchers working across education, human-computer interaction, and game studies, we have developed Ludolio, a digital platform designed to enable school and university libraries to make games accessible to students and educators. By positioning games as lendable, playable texts within library systems, Ludolio seeks to address a critical infrastructural barrier to game-based learning. In this presentation, we share key findings from interviews with teachers, co-design workshops with game developers and educators, and surveys, interviews, and observations with university students that informed the development of learning analytics, dashboard features, and curriculum materials that support teaching with games. Our aim is to contribute empirical evidence and design principles for integrating games into higher education teaching and learning infrastructures. Our research is informed by sociocultural theories of learning and game-based pedagogy, particularly theories that position learning as situated, participatory, and mediated by cultural tools (Lave & Wenger, 1991). From this perspective, games are understood as designed learning environments that invite players to engage in problem solving, narrative exploration, and identity experimentation (Burn, 2021). The study also draws on digital literacy and multiliteracies frameworks, which emphasise the importance of engaging learners with multimodal, interactive, and digitally mediated texts (Cope & Kalantzis, 2024; Ehret et al., 2022). Games are treated as complex cultural texts that combine narrative, mechanics, visuals, sound, and player agency, requiring new forms of literacy instruction and assessment. In addition, the research is shaped by participatory design and co-design theories, which positions educators as co-creators rather than end-users of educational technologies (DiSalvo et al., 2017). By involving educators in iterative design workshops, the project seeks to align technological affordances, such as dashboards and analytics, with pedagogical values rather than surveillance-oriented metrics (Selwyn, 2019). Finally, the study engages with emerging critiques of learning analytics, foregrounding ethical considerations related to transparency, agency, and meaningful interpretation of student data. Ludolio’s analytics are conceptualised not as measures of compliance, but as pedagogical supports that help educators understand how students engage with games as learning texts. Methodology, Methods, Research Instruments or Sources Used This study is guided by the following research questions: 1. How can a digital game lending platform support equitable access, pedagogical integration, and sustainable licensing models for games in schools and universities? And 2. How do educators conceptualise and co-design learning analytics and dashboard tools to support meaningful game-based pedagogy? This research adopts a design-based research methodology, combining iterative design, empirical investigation, and theory building (Design-Based Research Collective, 2003). DBR is particularly suited to examining complex educational innovations situated in real-world contexts, such as libraries and classrooms. The first phase involved a review of existing library acquisition models, digital rights management (DRM) practices, and educational game use. Semi-structured interviews were conducted with librarians and educators to identify current barriers to accessing and teaching with digital games. The second phase consisted of co-design workshops with school university educators across disciplines including education, media studies, and game design. Participants engaged in collaborative activities to prototype dashboard features, analytics visualisations, and pedagogical workflows. These workshops informed the iterative design of Ludolio’s teacher dashboard, including features for tracking engagement, supporting assessment design, and enabling reflective discussion around gameplay. Insights from the co-design process were integrated into successive iterations of the Ludolio platform. Key features include email-domain based authentication for simple institutional integration, flexible DRM that balances access with developer rights, and the ability for students to play both on campus and at home. Workshop artefacts, transcripts, and educator reflections were analysed using thematic analysis to identify recurring pedagogical priorities, concerns, and design principles. This analysis contributes to an emerging framework for library-based digital game lending and analytics-informed game-based pedagogy. Conclusions, Expected Outcomes or Findings This research makes several key contributions. First, it addresses a critical infrastructural gap by proposing and empirically examining a scalable model for digital game lending in school and university libraries. Second, it advances understanding of how co-designed learning analytics can support game-based pedagogy without reducing learning to reductive metrics. Third, it positions libraries as central actors in expanding equitable access to games as educational resources. Across interviews and co-design workshops, educators consistently emphasised that ease of access was foundational to pedagogical adoption. Privacy preserving, email-domain authentication and the ability for students to play across institutional and home contexts were identified as essential conditions for embedding games meaningfully into curricula. Educators also highlighted the importance of analytics that foreground pedagogical interpretation rather than performance surveillance. They valued indicators such as time spent exploring narrative spaces, progression patterns, and points of player decision-making, which supported reflective discussion and assessment design without prescribing learning outcomes. Importantly, findings suggest that positioning games within familiar library infrastructures reframes them as legitimate academic texts rather than extracurricular or optional resources. This shift enabled educators to articulate new assessment practices, support diverse learner participation, and advocate for the sustained inclusion of games within formal educational programs. By reimagining games as lendable, playable texts, our work contributes to broader conversations about digital literacies, educational technology design, and the future of libraries in higher education. It offers practical insights for educators, librarians, and researchers seeking to integrate games meaningfully into teaching and learning. References Burn, A. (2021). Literature, videogames and learning: Playing the text. Routledge. Cope, B., & M. Kalantzis. (2024). Multiliteracies: A literature review. In G. C. Zapata, M. Kalantzis, and B. Cope (Eds.), Multiliteracies in international education contexts (pp. 34–75). Routledge. Design-Based Research Collective. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5–8. DiSalvo, B., Yip, J., Bonsignore, E., & DiSalvo, C. (Eds.). (2017). Participatory design for learning: perspectives from practice and research. Routledge. Ehret, C., Mannard, E., & Curwood, J.S. (2022). How young adult video games materialize senses of self through ludonarrative affects: Understanding identity and embodiment through sociomaterial analysis. Learning, Media, and Technology, 47(3), 341-354. https://doi.org/10.1080/17439884.2022.2066125 Gee, J.P. (2003). What videogames have to teach us about learning and literacy. Palgrave Macmillan. Lave, J. & Wenger, E. (1991). Situated learning legitimate peripheral participation. Cambridge University Press. Selwyn, N. (2019). What's the problem with learning analytics? Journal of Learning Analytics, 6, 11–19. http://dx.doi.org/10.18608/jla.2019.63.3 Theodoulou, J., & Curwood, J.S. (2023). Play the game, live the story: Pushing narrative boundaries with young adult videogames. English Teaching: Practice and Critique, 22(2), 234-246. https://doi.org/10.1108/ETPC-08-2022-0105 | ||
