Sökning: "Kunskapsspårning"

Hittade 3 uppsatser innehållade ordet Kunskapsspårning.

1. 1. Attention based Knowledge Tracing in a language learning setting

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Sebastiaan Vergunst; [2022]
   Nyckelord :Knowledge Tracing; Exercise Recommendation; Personalised Learning; Recurrent Neural Network; Attention; Self-Attention; Exercise Embedding; Kunskapsspårning; Övningsrekommendation; Personligt Anpassad Inlärning; Rekurrenta Neurala Nätverk; Uppmärksamhet; Självuppmärksamhet; Övningsembedding;

   Sammanfattning : Knowledge Tracing aims to predict future performance of users of learning platforms based on historical data, by modeling their knowledge state. In this task, the target is a binary variable representing the correctness of the exercise, where an exercise is a word uttered by the user. LÄS MER

3. 2. Sequential Knowledge Tracing with Transformer Models

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Nino Yan-Nick Lucien Segala; [2022]
   Nyckelord :Knowledge Tracing; Transformers; Machine Learning; Exercise Recommendation; Sequential Model; Attention Model; Kunskapsspårning; Transformers; Maskininlärning; Övningsrekommendation; Sekventiell Modell; Uppmärksamhetsmodell;

   Sammanfattning : Transformer models, delivering big improvement in AI text-models (NLP), are now being applied in Knowledge Tracing to track the knowledge of students over time. One of the first, SAINT, showed quite some improvement over the then SOTA results on the public EdNet dataset and caused an increase in research based on transformer-based models. LÄS MER

4. 3. Dynamic Student Embeddings for a Stable Time Dimension in Knowledge Tracing

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Clara Tump; [2020]
   Nyckelord :Knowledge Tracing; Exercise Recommendation; Adaptive Learning; Machine Learning; Word Embeddings; Dynamic Embeddings; Recurrent Neural Networks; Long Short-Term Memory Neural Networks; Kunskapsspårning; Uppgiftsrekommendation; Adaptivt Lärande; Maskininlärning; Ordvektorer; Dynamiska Studentvektorer; Recurrent Neural Networks; Long ShortTerm Memory Neural Networks;

   Sammanfattning : Knowledge tracing is concerned with tracking a student’s knowledge as she/he engages with exercises in an (online) learning platform. A commonly used state-of-theart knowledge tracing model is Deep Knowledge Tracing (DKT) which models the time dimension as a sequence of completed exercises per student by using a Long Short-Term Memory Neural Network (LSTM). LÄS MER