ai-education
komi77-qwen2.5-0.5B_educational_instruct_low_start4400_max95p_new-3-GGUFkomi77-qwen2.5-0.5B_educational_instruct_gause_freq_max5.8p-3-GGUFkomi77-qwen2.5-0.5B_space_educational_instruct_low_start9150_max95p_new-3-GGUFkomi77-qwen2.5-0.5B_educational_instruct_uni5p-3-GGUFkomi77-qwen2.5-0.5B_space_educational_instruct_linear_max5.3p_new-3-GGUFHachipo-qwen2.5-0.5B_educational_instruct_selec5000_pythonblock_dataselection_enja-GGUFHachipo-qwen2.5-0.5B_educational_instruct_top3000_DeepL_ja-GGUFHachipo-qwen2.5-0.5B_educational_instruct_top3000_pythonblock_ja_en-GGUF
gen_ai_higher_education_datasetgen_ai_and_education_datasetAi_education_datasetLuganda-Linguistic-Knowledge-Benchmark
Luganda Linguistic Knowledge (LLK) Benchmark
Tests whether the model actually knows the Luganda language rules it is supposed to teach. Structured around CEFR levels with 75% of questions at foundational levels (A1–B1), heavily weighted toward Morphology & Concord (30%) and Syntax (25%) given Luganda's 12-noun-class agreement system. Includes C1–C2 stress tests for cultural context and advanced grammar. 100 mixed questions per language: multiple-choice (51), short-form (47), and… See the full description on the dataset page: https://huggingface.co/datasets/AI-for-Education/Luganda-Linguistic-Knowledge-Benchmark.Luganda-Linguistic-Pedagogical-Knowledge-Benchmark
Luganda Linguistic Pedagogical Knowledge (LLPK) Benchmark
Multiple-choice benchmark measuring whether a model understands how to teach foundational literacy in the Ugandan context. Built via a hybrid LLM-generation + human-review pipeline grounded in the global reading science (incl. the GEEAP report), the Ministry of Education P1 Luganda Teacher's Guide, and Pilkington's 1915 A Handbook of Luganda. Generated with Gemini 2.5 Flash and validated by an education expert and native… See the full description on the dataset page: https://huggingface.co/datasets/AI-for-Education/Luganda-Linguistic-Pedagogical-Knowledge-Benchmark.ruTeacherTalkHere, we present a dataset of 90 lesson transcripts annotated with 14 teacher talk moves.
The lessons were given in Russian non-selective public schools. The teacher talk moves are
divide in two groups: sociological and methodological ones.
Sociological moves: Marking the symbolic boundaries of a lesson, Addressing a specific student,
Markers of power, I-mode, We-mode, Expression of praise, Expression of disapproval.
Methodological moves: Beginning of a class, Maintaining discipline… See the full description on the dataset page: https://huggingface.co/datasets/ai-education/ruTeacherTalk.