Learners can differ in a number of ways. However, in current education differences are rarely taken into account, which means that courses are the same for all learners. Differences between individuals are a starting point to personalize a learning trajectory. There is evidence in the literature that fitting support and feedback to the needs of the learner have positive effects on the quality and pace of learning. This study aims to contribute to this line of research by exploring a combination of learning strategies that adapt to the learner's characteristics.
The aim of this study is to test the effectiveness of a personalized learning program as a combination of adjusting (a) the difficulty of exercises, and (b) the nature of the feedback. Both are adapted to the learner's level of performance. The learning task in this study is the game “Space Fortress” (Agarwal et al., 2018; Mané & Donchin, 1989). The effects of personalized learning strategies are examined on the learning progress and learning outcome, by comparing the results of a standardized learning program (non-personalized) with those of a personalized learning program. The learning program took five hours extended over two weeks. A quasi-experimental pre-test - training - post-test control group study was conducted among forty participants randomly assigned to the control condition (standardized learning program) and the experimental condition (the personalized learning program). The average age of the participants is 24 years. Participants were recruited through the TNO database.
Before the learning program started, participants' self-efficacy was measured using the Motivated Strategies for Learning Questionnaire (Pintrich, Smith, García, & McKeachie, 1991) and the aiming task pretest was administered to participants. After the completion of the learning program, motivation was measured with the Intrinsic Motivation Inventory (Deci & Ryan, 1982) and the learning experience with the Personalized Learning Environment Questionnaire (Waldrip et al., 2014), the aiming task posttest was administered to participants. The learning progress was measured by the performance (pre, mid, post) on the learning tasks, the learning performance was measured by the performance on the complete Space Fortress game (Frederiksen & White, 1989) and the explanatory factor for the performance on the complete Space Fortress game by means of the aiming task on the pretest (Mané & Donchin, 1989).
The ANCOVA showed that participants from the experimental condition did not have a higher performance level on the posttest than participants in the control condition. The repeated measures ANOVAs have shown that participants in the experimental condition had no faster progress than participants in the control condition. The T-test showed that no difference was found in how participants in the control condition and the experimental condition assessed the training, according to their learning needs. The Multiple Regression Analysis revealed that both self-efficacy and motivation were not predictors of performance on the entire Space Fortress game.
In this study, a complete learning program was developed in which the adjustments were monitored and analyzed fully automatically and in real time, and adaptations were implemented fully automatically in the learning program. Contrary to what the literature indicated, this study has shown that a personalized learning program does not lead to a faster and better acquisition of complex skills than a standardized learning program. Possible explanations that have influenced the results are the lack of interactive multimedia instructions, user control and information about the state of the learner.
|Date of Award||10 Jun 2020|
|Supervisor||Hendrik Drachsler (Supervisor)|
- personalized learning
- learning strategies
- adaptive learning environment
- learner characteristics
- learning analytics