Adaptive e-Learning: Towards a Metacomprehension Approach.

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Autor/in	Vössing, Julia
Titel	Adaptive e-Learning: Towards a Metacomprehension Approach.
Quelle	Berlin: Freie Universität Berlin (2016), XII, 136 S. PDF als Volltext kostenfreie Datei (1); PDF als Volltext kostenfreie Datei (2) Link als defekt meldenVerfügbarkeit Dissertation, Freie Universität Berlin, 2016.
Sprache	englisch
Dokumenttyp	online; Monographie
URN	urn:nbn:de:kobv:188-fudissthesis000000102700-5
Schlagwörter	Vergleich; Bewertung; Dissertation; Lernen; Computerunterstützter Unterricht; Vergleich; E-Learning; Lernen; Computerunterstützter Unterricht; Dissertation; E-Learning; Bewertung
Abstract	This dissertation presents work contributing to a further improvement of e-learning using a metacomprehension approach. Research interest is increasing in using metacomprehension judgments (e.g., judgments of learning, JOL) in computer-assisted learning. The usefulness of such judgments as tools for research or for learner support hinges on their accuracy, which is notoriously low. Although JOL generally predict learning performance their accuracy seems to be influenced both by features of the learning material (e.g. amount and size of text) and by personal factors (e.g. self-efficacy). This dissertation therefore aims to sustainably boost metacomprehension accuracy as a vital requirement for further improving self-regulated computer-supported learning. The rationale of Study I was that of a manipulation to increase experience-based judgments and decrease theory-based judgments. In terms of an experimental manipulation, the question therefore was whether judgments of difficulty (JOD) administered before the JOL proper influence JOL accuracy. In the simple judgments group, participants rated the likelihood of answering correctly a knowledge question on e-learning chapters (JOL). In the combined judgments group, participants rated text difficulty (JOD) before making a JOL. In the first experiment no accuracy differences emerged, but additional analyses showed that the judgment manipulation had induced cognitive processing differences. Therefore, in the second experiment of Study I judgment scope was manipulated. Both judgment accuracy and knowledge test scores were higher in the combined judgments group with term-specific judgments. Study II sought to add knowledge about text difficulty effects on metacomprehension accuracy. Sequences of chapters with the same text difficulty and sequences of chapters with randomly varying text difficulty may entail different anchors and thus prime higher or lower JOL accuracies, respectively. The general tenet was that orders would trigger different extents of experience-based processing and thus influence metacomprehension accuracy to different degrees. To investigate the impact of text difficulty on metacomprehension accuracy and learning performance four groups of learners who perform e-learning differing in blocking type (blocked vs. mixed) and difficulty sequence (rising vs. declining) of text material were compared. As hypothesized, accuracy was higher for blocked difficulty orders. Late-section judgment magnitude decreased more strongly in the blocked groups. At the same time, late-section judgment accuracy was higher in the blocked group. Finally, Study III extended the previous findings by analysing the impact of the so called multimedia heuristic on judgment accuracy. For that purpose, a conceptual images group was compared to a decorative images group and a text-only group. Depending on the condition either conceptual images summarizing the chapters´ content or decorative images without any relevant information were added to the e-learning. The control group worked on a text-only version of the same e-learning unit. As postulated, combined JOL benefitted accuracy and knowledge test scores; both were highest in the conceptual images group. In Experiment 2 of Study III, to further increase accuracy, judgment scope was changed from global to specific. Again, accuracy and test scores were highest in the conceptual images group. Contrary to expectations, however, JOL accuracy did not benefit from term-specific judgments. In sum, the work presented in the this dissertation demonstrates ways to sustainably boost metacomprehension accuracy and thereby establishes the requirements needed to use the metacomprehension approach for personalizing e-learning and increasing its learning efficiency as well as effectiveness. (Orig.).
Erfasst von	Deutsche Nationalbibliothek, Frankfurt am Main
Update	2017/1