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Sample Selector

Sample Selector is a tool for creating and editing samples, or groups of data you compare across—they're not "samples" in the statistical sense, but more like filters.

By default, a single sample exists: "All Data". With the Sample Selector, you can create new samples to organize your data.

You can use samples to:

A sample is composed of one or more filters, specific conditions that narrow down your sample.

Creating a sample

The general process for creating a sample is to:

The effect of multiple filters

DataShop interprets each filter after the first as an additional restriction on the data that is included in the sample. This is also known as a logical "AND". You can see the results of multiple filters in the sample preview as soon as all filters are "saved".

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SelfCode 2.0: Annotated Corpus of Student Self-Explanations to Introductory JAVA Programs in Computer Science (private) (gold star)

Datasets Terms of Use

PI
Arun Balajiee Lekshmi Narayanan
Data Provider
Description
Assessing student responses is a critical task in adap-
tive educational systems. More specifically, automati-
cally evaluating students’ self-explanations contributes
to understanding their knowledge state which is needed
for personalized instruction, the crux of adaptive edu-
cational systems. To facilitate the development of Ar-
tificial Intelligence (AI) and Machine Learning models
for automated assessment of learners’ self-explanations,
annotated datasets are essential. In response to this
need, we developed the SelfCode2.0 corpus, which con-
sists of 3,019 pairs of student and expert explanations of
Java code snippets, each annotated with semantic sim-
ilarity, correctness, and completeness scores provided
by experts. Alongside the dataset, we also provide per-
formance results obtained with several baseline models
based on TF-IDF and Sentence-BERT vectorial repre-
sentations. This work aims to enhance the effectiveness
of automated assessment tools in programming education and contribute to a better understanding and supporting student learning of programming

Tags
Natural Language Processing, Introductory Programming, JAVA, Self Explanations, LLMs, BERT

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External Links
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Datasets
Dataset Area/ Subject Dates Data Last Modified Transactions KC Models Status Papers
Computer Science/ Introductory Programming: Java Aug 1, 2018 - Dec 31, 2023 - 0 0 files-only 1