Do Data Scientists Dream About Their Skills’ Assessment? – Transforming a Competition Platform Into an Assessment Platform

We present a platform for automatic assessment of technical data science skills (hard skills) and competencies that help to apply those technical skills in practice (soft skills). The platform serves so-called assessment platform tasks that resemble data-focused tasks typical for online data science competitions. Actually, these tasks are designed based on international conference competitions that we have been organizing on our competition platform knowledgepit.ai. The main idea relies on our observation that the given person’s behavior during a competition (dynamics of submitting solutions, activity on competition forum, etc.) can be correlated with his/her soft competencies. Accordingly, our goal is to translate the specifics of international conference competitions into a framework that investigates the behaviors of data science job candidates, employees who want to improve their work in data science projects, students who wish to build their future professional careers on AI solutions, etc. We claim that such behaviors – if properly measured based on solving our assessment platform tasks – can effectively indicate both hard and soft types of competencies.

Authors

Institutions

Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10825378
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
1.06
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Do Data Scientists Dream About Their Skills’ Assessment? – Transforming a Competition Platform Into an Assessment Platform

Agnieszka Chądzyńska-Krasowska, Andrzej Janusz, Jacek Kamiński, Dominik Ślȩzak et al.
2 citations
Big Data and Business Intelligence
1.06
article

Do Data Scientists Dream About Their Skills’ Assessment? – Transforming a Competition Platform Into an Assessment Platform

Agnieszka Chądzyńska-Krasowska, Andrzej Janusz, Jacek Kamiński, Dominik Ślȩzak, Maciej Świechowski
article en
2 citations

Abstract

We present a platform for automatic assessment of technical data science skills (hard skills) and competencies that help to apply those technical skills in practice (soft skills). The platform serves so-called assessment platform tasks that resemble data-focused tasks typical for online data science competitions. Actually, these tasks are designed based on international conference competitions that we have been organizing on our competition platform knowledgepit.ai. The main idea relies on our observation that the given person’s behavior during a competition (dynamics of submitting solutions, activity on competition forum, etc.) can be correlated with his/her soft competencies. Accordingly, our goal is to translate the specifics of international conference competitions into a framework that investigates the behaviors of data science job candidates, employees who want to improve their work in data science projects, students who wish to build their future professional careers on AI solutions, etc. We claim that such behaviors – if properly measured based on solving our assessment platform tasks – can effectively indicate both hard and soft types of competencies.

Polish-Japanese Academy of Information Technology (PL)
Openalex Percentile: Top 15%
Big Data and Business Intelligence
1.06
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.