We present the results of a study where we provided students with textual explanations for learning content recommendations along with adaptive navigational support, in the context of a personalized system for practicing Java programming. We evaluated how varying the modality of access (no access vs. on-mouseover vs. on-click) can influence how students interact with the learning platform and work with both recommended and non-recommended content. We found that the persistence of students when solving recommended coding problems is correlated with their learning gain and that specific student-engagement metrics can be supported by the design of adequate navigational support and access to recommendations' explanations.
Description
Adaptive Navigational Support and Explainable Recommendations in a Personalized Programming Practice System | Proceedings of the 34th ACM Conference on Hypertext and Social Media
%0 Conference Paper
%1 Barria_Pineda_2023
%A Barria-Pineda, Jordan
%A Akhuseyinoglu, Kamil
%A Brusilovsky, Peter
%B Proceedings of the 34th ACM Conference on Hypertext and Social Media
%D 2023
%I ACM
%K explanations ht2023 navigation-support recommender
%P 1-9
%R 10.1145/3603163.3609054
%T Adaptive Navigational Support and Explainable Recommendations in a Personalized Programming Practice System
%U https://doi.org/10.1145%2F3603163.3609054
%X We present the results of a study where we provided students with textual explanations for learning content recommendations along with adaptive navigational support, in the context of a personalized system for practicing Java programming. We evaluated how varying the modality of access (no access vs. on-mouseover vs. on-click) can influence how students interact with the learning platform and work with both recommended and non-recommended content. We found that the persistence of students when solving recommended coding problems is correlated with their learning gain and that specific student-engagement metrics can be supported by the design of adequate navigational support and access to recommendations' explanations.
@inproceedings{Barria_Pineda_2023,
abstract = {We present the results of a study where we provided students with textual explanations for learning content recommendations along with adaptive navigational support, in the context of a personalized system for practicing Java programming. We evaluated how varying the modality of access (no access vs. on-mouseover vs. on-click) can influence how students interact with the learning platform and work with both recommended and non-recommended content. We found that the persistence of students when solving recommended coding problems is correlated with their learning gain and that specific student-engagement metrics can be supported by the design of adequate navigational support and access to recommendations' explanations.},
added-at = {2023-10-17T17:52:26.000+0200},
author = {Barria-Pineda, Jordan and Akhuseyinoglu, Kamil and Brusilovsky, Peter},
biburl = {https://www.bibsonomy.org/bibtex/2cb7874b368652bc7db413874891bd86f/brusilovsky},
booktitle = {Proceedings of the 34th {ACM} Conference on Hypertext and Social Media},
description = {Adaptive Navigational Support and Explainable Recommendations in a Personalized Programming Practice System | Proceedings of the 34th ACM Conference on Hypertext and Social Media},
doi = {10.1145/3603163.3609054},
interhash = {1cb83a389218d6270c932e04ee7e114f},
intrahash = {cb7874b368652bc7db413874891bd86f},
keywords = {explanations ht2023 navigation-support recommender},
month = sep,
pages = {1-9},
publisher = {{ACM}},
timestamp = {2023-10-17T17:52:26.000+0200},
title = {Adaptive Navigational Support and Explainable Recommendations in a Personalized Programming Practice System},
url = {https://doi.org/10.1145%2F3603163.3609054},
year = 2023
}