Self-regulated learning (SRL) requires learners’ active participation, i.e., they need to activate cognitive and metacognitive learning strategies. These strategies can be activated and supported by using cognitive and metacognitive prompts. Extensive research concerning the effects of prompts on SRL is necessary to determine connections between these two concepts. Our study investigates the effects of cognitive and metacognitive activities—i.e., prompts—on learning performance during SRL. Therefore, we developed three types of learning environments that use different types of prompts—cognitive or metacognitive prompts—or no prompts. Moreover, we also used a questionnaire to examine prior knowledge and post-knowledge. Pre- and post-tests show that self-confidence in prior knowledge has a significant effect on self-confidence in post-knowledge, cognitive prompts reduce extrinsic motivation, and knowing how to use cognitive learning strategies enables using cognitive prompts more effectively. These results are partially in line with existing research findings on the effects of prompts in SRL.

We assume that learners generate self-reference to a topic dealt with in class through motivational prompts of a pedagogical agent (PA). This assumption is based on self-determination theory and organismic integration theory. Consequently, learners are more motivated and achieve better learning results. We examined the influence of motivational prompts on learning success and motivation in a digital learning environment. Therefore, we implemented a PA within a web-based learning environment in order to scaffold learners’ autonomous motivation. In an experimental pre-post design (n = 60), learning success and motivation were analyzed comparing learning environments with and without PA/prompting. Results suggest that learners with a PA reach a higher level of knowledge than learners without a PA. There was no significant influence of motivational prompts on motivation itself. The limitations and conclusions of this study are discussed.

Effectively managing cognitive demands during problem solving is crucial for academic success. While instructional design research offers strategies to support learners, the effects of task complexity and pre-training on cognitive processes and performance require further investigation. This study reports on four experiments to examine their individual and combined effects on problem-solving performance, cognitive load, and mental effort. Participants completed three task rounds with either high or increasing complexity. Cognitive load and mental effort were assessed using self-report questionnaires, and performance was measured in the final round. Across three experiments, pre-training was provided and compared with a condition without pre-training. Results indicated that consistently high task complexity tended to be associated with lower cognitive load and mental effort than gradually increasing complexity. However, the effects of task complexity on performance were not consistent across experiments. Pre-training was associated with fewer moves needed to solve the task, whereas effects on completion time, cognitive load, and mental effort varied across experiments. No significant interaction effects between task complexity and pre-training were observed.

This paper presents two experiments examining the influences of media-specific appraisal and attribution on multimedia learning. The first experiment compares four different versions of learning material (text, text with images, animation with text, and animation with audio). Results reveal that the attributed type of appraisal, (i.e., the subjective impression of whether a medium is easy or difficult to learn with) impacts invested mental effort and learning outcomes. Though there was no evidence for the modality effect in the first experiment, we were able to identify it in a second study. We were also able to replicate appraisal and attribution findings from study 1 in study 2: if media appraisal leads to the result that learning with a specific medium is difficult, more mental effort will be invested in information processing. Consequently, learning outcomes are better, and learners are more likely to attribute knowledge acquisition to their own abilities. Outcomes also indicate that the modality effect can be explained by avoidance of split-attention rather than modality-specific information processing in working memory.

Although there is abundant empirical evidence that, separately applied, cognitive load theory and desirable difficulty theory enhance performance, little is known about how these theories can be successfully combined. To address this critical gap, the present study investigated the effects of complexity (constantly high vs. gradually increasing) and desirable difficulty (interleaved vs. blocked) on performance, metacognitive strategy use, and self- and task perception. In total, 132 learners participated in this 2 × 2 factorial intervention study. This study consisted of a main learning session and a posttest two days later. The posttest results showed that confronting learners with complex desirable difficulty tasks was effective in fostering performance. Furthermore, cognitive load was revealed as one of the major reasons for learners’ metacognitive engagement. We discuss the implications of these findings for research, theory, and practice and provide recommendations for future research.