@inproceedings{62cb9361a53242d284c5199ceb09099c,
title = "Real-Time Visual Feedback: A Study in Coding Analytics",
abstract = "Higher dropout and failure rates among computer science students in introductory programming courses tend to be a norm for many institutions. Years of evidence indicate that dropouts and failures persist in spite of advancements in pedagogy, technology, and teacher training. Most advancements have relied on summative assessments and of late formative assessments. This research explores assessments computed from real-time measures, based on observational data collected during student engagement with study and remedial activities. An experiment was conducted to measure the impact of real-time code assessment and dashboard-based feedback in the domain of Programming. Results indicate better course grades for a small percentage of students, and the need for task-level and meta-level interactions to guarantee significant and persistent academic performance and programming mastery.",
keywords = "coding analytics, formative, interactive dashboard, performance, self-regulation, sommative",
author = "Jeremie Seanosky and Isabelle Guillot and David Boulanger and Rebecca Guillot and Claudia Guillot and Vivekanandan Kumar and Fraser, {Shawn N.} and Kinshuk and Nahla Aljojo and Asmaa Munshi",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 17th IEEE International Conference on Advanced Learning Technologies, ICALT 2017 ; Conference date: 03-07-2017 Through 07-07-2017",
year = "2017",
month = aug,
day = "3",
doi = "10.1109/ICALT.2017.38",
language = "English",
series = "Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017",
pages = "264--266",
editor = "Ronghuai Huang and Radu Vasiu and Kinshuk and Sampson, {Demetrios G} and Nian-Shing Chen and Maiga Chang",
booktitle = "Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017",
}