Moses, K. R. (2019, June), Board 22: The Effects of Mobile Circuits on Student Learning Outcomes: Evidence from Real-time Time-stamped Interaction Data  Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32301

\bibitem{asee_peer_32301}
  Moses, K. R. (2019, June), \emph{Board 22: The Effects of Mobile Circuits on Student Learning Outcomes: Evidence from Real-time Time-stamped Interaction Data}
  Paper presented at 2019 ASEE Annual Conference \& Exposition , Tampa, Florida.
  10.18260/1-2--32301

Kenie R. Moses.  "Board 22: The Effects of Mobile Circuits on Student Learning Outcomes: Evidence from Real-time Time-stamped Interaction Data".  2019 ASEE Annual Conference & Exposition , Tampa, Florida, 2019, June.  ASEE Conferences, 2019.  https://peer.asee.org/32301 Internet.  15 Dec, 2024

\bibitem{asee_peer_32301}
  Kenie R. Moses.
  "Board 22: The Effects of Mobile Circuits on Student Learning Outcomes: Evidence from Real-time Time-stamped Interaction Data".
  \emph{2019 ASEE Annual Conference \& Exposition , Tampa, Florida, 2019, June}.
  ASEE Conferences, 2019.
  https://peer.asee.org/32301 Internet.  15 Dec, 2024

@INPROCEEDINGS{asee_peer_32301
author = "Kenie R. Moses"
title = "Board 22: The Effects of Mobile Circuits on Student Learning Outcomes: Evidence from Real-time Time-stamped Interaction Data"
booktitle = "2019 ASEE Annual Conference \& Exposition "
year = "2019"
month = "June"
address = "Tampa, Florida"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/32301}
number = {10.18260/1-2--32301}
}

TY  - CPAPER
AB  - This research paper presents a microscopic view of students’ interactions with CircuitITS (CITS), a mobile learning environment-based (MLE) tutoring system that scaffolds students’ circuits analysis process and Circuit Test Taker (CTT), an MLE-based test-taking tutoring system for circuit analysis that provides full-step solutions at the end of each simulated exam. The specific user behavior considered in this study was duration and frequency of use, the number of scaffolds (hints) utilized per problem and the level of difficulty of problems solved when using the MLE tutor. Scores from three examinations were recorded from all students throughout the semester. Multilevel longitudinal modeling was used to assess effects of the MLE on student exam scores over three examination periods. Results suggest that number of scaffolds utilized per problem, as well as the level of difficulty of the problems solved while using the tutors significantly increased student achievement during the semester. This research proposed that MLEs, digital assistive technology and learner analytics have the potential to increase student problem-solving performance and achievement through learning analytics and instructional strategies.
AU  - Kenie R. Moses
CY  - Tampa, Florida
DA  - 2019/06/15
PB  - ASEE Conferences
TI  - Board 22: The Effects of Mobile Circuits on Student Learning Outcomes: Evidence from Real-time Time-stamped Interaction Data
UR  - https://peer.asee.org/32301
DO  - 10.18260/1-2--32301
ER  -