Recent theories assume a mutual facilitation in case of semantic overlap for concepts being activated simultaneously. We provide evidence for this claim using a semantic priming paradigm. To test for mutual facilitation of related concepts, a perceptual identification task was employed, presenting prime-target pairs briefly and masked, with an SOA of 0 ms (i.e., prime and target were presented concurrently, one above the other). Participants were instructed to identify the target. In Experiment 1, a cue defining the target was presented at stimulus onset, whereas in Experiment 2 the cue was not presented before the offset of stimuli. Accordingly, in Experiment 2, a post-cue task was merged with the perceptual identification task. We obtained significant semantic priming effects in both experiments. This result is compatible with the view that two concepts can both be activated in parallel and can mutually facilitate each other if they are related.

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Research suggests that explanatory pictures support learning, whereas pictures that distract processing resources from the main ideas of a text may impair learning and are considered as seductive illustrations. However, non-explanatory pictures that are related to the text and that do not tempt readers to focus illustrations more than the text’s main ideas might improve learning through spreading activation processes during learning. This effect might be reflected in memory measures or in metacognitive measures. Therefore, in two experiments, we tested related decorative pictures for positive effects on knowledge and transfer performance and metacognitive monitoring. Results indicate positive effects of related pictures on knowledge acquisition (Experiment 1) and metacognitive monitoring (Experiment 2). In neither experiment, related pictures enhanced transfer performance or interest (measured as triggered and maintained situational interest). This pattern of results can be explained by automatic mutual facilitation of related materials based on spreading activation processes.

IntroductionResults from experimental research in instructional psychology imply that a deep menu structure of a e-learning website may provide useful segmentation. However, menu depth also increases the need for navigation and thus, might have impairing effects on learning. Furthermore, instructional support can be provided by including a checklist, to ensure that learners reflect on their study progress. The study aimed at investigating which menu structure is beneficial for e-learning websites and whether a checklist could compensate the negative effects of an unfavorable menu structure.MethodsTherefore, in an online experiment, we let 101 students learn facts about rocks from an e-learning website with either a deep or a flat menu structure. We further manipulated whether metacognitive support through a checklist was provided or not. Learning outcomes, cognitive load, metacognitive factors as well as learning time were measured.ResultsResults show no main effects of the menu depth or the presence of a checklist on retention and transfer performance. Learning achievements in percent for retention were 37.31 (deep menu/checklist), 31.10 (deep menu/no checklist), 36.07 (flat menu/checklist), 38.13 (flat menu, no checklist) and for transfer were 35.19 (deep menu/checklist), 34.40 (deep menu/no checklist), 37.78 (flat menu/checklist), 33.23 (flat menu, no checklist). Yet, there are hints that the deeper menu structure had a negative effect on learning processes: The deep menu structure led to an enhanced extraneous cognitive load (ECL) and reduced learning efficiency. However, providing a checklist had beneficial effects mainly when learning with a deep menu structure but not overall. Unexpectedly, the presence of the checklist did not influence metacognitive measures.DiscussionOur study suggests that possible costs of a deep menu structure should be considered when designing instructional checklists. However, the study also provides a way in which these costs can be compensated, which is by using a checklist. Implications for instructional research and e-learning are discussed.

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