A Post-COVID-19 VLog

The idea of this VLog

As part of the digiTED Project’s commitment to fostering collaboration and innovation in teacher education, Project Result 6 presents a rich exploration of stakeholder perspectives on hybrid learning, digital tools, and the future of teacher education with a focus on the teacher educator profesion. Led by the University of Education Ludwigsburg, this initiative brings together voices from educators and EdTech developers in a dynamic Vlog series, as well as a thematic analysis paper. This in-depth research captures the challenges and opportunities in the post-COVID-19 educational landscape, while also addressing the rapid rise of AI and digital transformation.

Emerging Trends

The accompanying paper offers a structured thematic analysis of interview findings, making the insights accessible to a broader audience. To expand impact and accessibility, the team also piloted the use of AI software (NotebookLM) to generate a podcast based on the research — an innovative step toward engaging wider audiences in the ongoing conversation around digitalisation in teacher education.

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See note below.

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Note on the AI-generated podcast: The podcast was created using the AI-Software NotebookLM as a trial to explore its potential for summarising and disseminating findings from Project Result 6. It provides an overview of the key insights from the seven interviews conducted as part of the digiTED Vlog. Importantly, only the anonymised transcripts – without any names – were used as the basis for generating the podcast. To ensure accuracy and ethical considerations, the factual content was thoroughly checked. No major errors were identified in the AI-generated summary; however, a few minor issues were noted. Firstly, the digiTED project was mistakenly referred to as a research project when it is, in fact, an Erasmus+ initiative. Secondly, the AI sometimes assigned incorrect gender pronouns, occasionally referring to someone as “he” instead of “she” or vice versa. Additionally, any metaphors or figurative language used in the podcast were AI-generated and do not necessarily reflect the original wording of the interviewees. Another minor discrepancy is that the podcast places more emphasis on the topic of research than was actually present in the interviews. While research was discussed to some extent, it was not as prominent as the podcast suggests. Similarly, the issue of inequality – while touched upon in a different context – was not as central in the interviews as the AI-generated podcast portrays it to be. Leadership was also overstated; while it was explicitly mentioned once, the podcast implies a broader discussion, including the notion that leaders need to articulate a vision – something that was not mentioned by the interviewees. Additionally, the concept of communities of practice was not explicitly discussed in the interviews. However, some interviewees implicitly referred to similar ideas, particularly when discussing collaborative learning, knowledge sharing, and professional networks. The AI, however, framed this theme as if it were a core, explicit discussion point. These observations highlight a key challenge in AI-generated content – certain themes may be unintentionally amplified or underrepresented. Despite these minor inaccuracies, the podcast effectively conveys the main discussions and serves as an accessible format for wider dissemination.