Publication Date


Document Type


First Advisor

Xie, Ying

Degree Name

Ph.D. (Doctor of Philosophy)

Legacy Department

Department of Educational Technology, Research and Assessment (ETRA)


This experimental research study examined the effects of using a mobile learning environment (MLE) that provided scaffolded assistive tutoring on student achievement in a Circuit Analysis (Network Theory) course. It also aimed to examine the relationships between students’ user learning analytics and their learning outcomes. The design and development of the mobile app was based on the Model of Contingent Instruction and Metacognitive Support which critically applies scaffolding as its operative in transferring domain knowledge in expert to novice problem-solving.

This experimental research study collected data from eighty-three undergraduate college students who were randomly assigned into one of three groups and participated in the study for an entire semester. The control group did not have access to the application. Participants in Treatment I group used the test-only version of the application (an exclusively test-taking intervention with full solutions at the end of the test). Participants in Treatment II group used the full version of the application (a per-problem scaffolded solution intervention that also included the ability to take tests). Scores from three examinations were recorded from all students throughout the semester and among those who utilized the application, user interaction data and survey data pertaining to problems-solving and technology-use self-efficacy was collected. Multilevel modeling was used to assess the effects of the assistive MLE tutor on student achievement, problem-solving and technology-use self-efficacy. In addition, multilevel modeling was used to assess effects of user interaction data on student examination scores.

The results of this study showed statistically significant effects of the treatment in mean student achievement (examination scores) overall, and at each time point. Analysis of user interaction data from this study showed that the number of scaffolds utilized per problem, as well as the duration and frequency of intervention use did not predict student exam scores. However, the level of difficulty of the problems solved while using the assistive MLE did significantly and positively predict student exam scores. Furthermore, results showed a significant negative effect of the scaffolding MLE tutor (CITS) on NTSEI scores compared to CTT and significant positive relationship of NTSEI scores with exam scores.

With digital technologies and learning analytics emerging at the forefront of educational research, the inclusion of these tools may benefit practitioners, designers and researchers through the development of curricula that leverages this research in conjunction with student-centered learning. This research suggests that with deployment of ubiquitous MLEs, digital assistive technology and learner analytics have the potential to increase engineering students’ problem-solving performance and achievement through the analysis of user behavior data, sustained problem-solving practice and the reinforcement of engineering theories.


248 pages




Northern Illinois University

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