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Research on conceptual change, learning from errors, and ‘productive failure’ suggests that elaborating on errors during instruction is crucial for learning in settings which put problem solving before instruction. To reveal the role of elaboration and comparison of errors, we investigated the effect of prompting students to engage in such cognitive processes: Students in all conditions first worked on an identical problem-solving activity (targeting the comparison of fractions) without prior instruction about the targeted concepts and procedures. In the subsequent instruction phase, students in the different conditions received 1) only correct solutions, 2) correct and erroneous examples, or 3) additional comparison prompts. Students who were prompted to compare erroneous solution attempts to correct solutions significantly outperformed their peers at posttest. Elaborating on errors seemed to mediate this effect. In accordance with the theoretical assumptions, the difference between conditions was only significant for students whose initial solution resembled the erroneous examples.

Research on diagnostic competencies of teachers nowadays raises the question which person or situational characteristics moderate judgement accuracy. Beside this correlational approach, a stronger interest in understanding the cognitive processes involved in the genesis of diagnostic judgements has emerged. To address the theoretical gap regarding cognitive processes underlying diagnostic judgements, we propose a framework, called DiaCoM (Explaining Teachers’ Diagnostic Judgements by Cognitive Modeling). It aims at supporting (existing or envisioned) research that strives to test cognitively oriented explanations for processes and products of diagnostic judgements of teachers.

Affective states play a significant role in students’ learning behaviour. Positive affective states can enhance learning, whilst negative affective states can inhibit it. This paper describes a Wizard-of-Oz study which investigates whether the way feedback is presented should change according to the affective state of a student, in order to encourage affect change if that state is negative. We presented high-interruptive feedback in the form of pop-up windows in which messages were immediately viewable; or low-interruptive feedback, a glow-\ud ing light bulb which students needed to click in order to access the messages. Our results show that when students are confused or frustrated high-interruptive feedback is more effective, but when students are enjoying their activity, there is no difference. Based on the results, we present guidelines for adaptively tailoring the presentation of feedback based on students’ affective states when interacting with learning environments.

Recent studies have shown benefits of problem-solving prior to instruction (cf. productive failure) for learning. These findings seem to contradict well-established assumptions of cognitive load theory. However, there are two possible mechanisms in line with cognitive load theory that may explain these beneficial effects: the activation of prior knowledge and intuitive ideas during the problem-solving phase to generate solution approaches and the focusing of attention on relevant components of the canonical solution by comparing and contrasting typical student solutions to the canonical solution during the instruction phase. It is unclear whether the reported benefits originate from the activation of prior knowledge and intuitive ideas during the problem-solving phase or from the specific form of instruction in which student solutions are compared and contrasted to the canonical solution. To investigate this question, we compared three conditions in a quasi-experimental study: standard instruction prior to problem-solving (I − PS), instruction in which typical student solutions are contrasted to the canonical solution prior to problem-solving (Icontrast − PS), and problem-solving prior to instruction in which typical student solutions are contrasted to the canonical solution (PS − Icontrast). I − PS was outperformed by the other two conditions on conceptual knowledge. This finding suggests that student solutions are fruitful learning resources. We argue that the comparison of student solutions and the canonical solution focuses attention on the relevant components of the solution, which leads to deeper processing. Indeed, our cognitive load measures suggest that comparing and contrasting typical student solutions during instruction is germane for learning.

We describe a Wizard-of-Oz study that investigates the impact of different types of feedback on students’ affective states. Our results indicate the importance of matching carefully the affective state with appropriate feedback in order to help students transition into more positive states. For example when students were confused affect boosts and specific instruction seem to be effective in helping students to be in flow again. We discuss this and other effective ways to and implications for the development of our system and the field in general.