English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Student commitment towards a learning recommendation is not separable fromtheir understanding of the reasons it was recommended to them; and theirability to modify it based on that understanding. Among explainabilityapproaches, chatbots offer the potential to engage the student in aconversation, similar to a discussion with a peer or a mentor. The capabilitiesof chatbots, however, are still not sufficient to replace a human mentor,despite the advancements of generative AI (GenAI) and large language models(LLM). Therefore, we propose an approach to utilize chatbots as mediators ofthe conversation and sources of limited and controlled generation ofexplanations, to harvest the potential of LLMs while reducing their potentialrisks at the same time. The proposed LLM-based chatbot supports students inunderstanding learning-paths recommendations. We use a knowledge graph (KG) asa human-curated source of information, to regulate the LLM's output throughdefining its prompt's context. A group chat approach is developed to connectstudents with human mentors, either on demand or in cases that exceed thechatbot's pre-defined tasks. We evaluate the chatbot with a user study, toprovide a proof-of-concept and highlight the potential requirements andlimitations of utilizing chatbots in conversational explainability.

Supporting Student Decisions on Learning Recommendations: An LLM-Based  Chatbot with Knowledge Graph Contextualization for Conversational  Explainability and Mentoring