@phdthesis{Greving2022,
  author    = {Greving, Carla Elisabeth},
  title     = {Improving Learning from Texts: Distributed Practice and Distributed Learning as Desirable Difficulty in Reading Single and Multiple Texts},
  doi       = {10.25972/OPUS-29685},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-296859},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {Distributed practice is a well-known learning strategy whose beneficial effects on long-term learning are well proven by various experiments. In learning from texts, the benefits of distribution might even go beyond distributed practice, i.e. distribution of repeated materials. In realistic learning scenarios as for example school or university learning, the reader might read multiple texts that not repeat but complement each other. Therefore, distribution might also be implemented between multiple texts and benefit long-term learning in analogy to distributed practice. The assumption of beneficial effects of this distributed learning can be deduced from theories about text comprehension as the landscape model of reading (van den Broek et al., 1996) in combination with theories of desirable difficulties in general (R. A. Bjork \& Bjork, 1992) and distributed practice in particular (Benjamin \& Tullis, 2010). This dissertation aims to investigate (1) whether distributed learning benefits learning; (2) whether the amount of domain-specific prior knowledge moderates the effects of distribution, (3) whether distributed learning affects the learner's meta-cognitive judgments in analogy to distributed practice and (4) whether distributed practice is beneficial for seventh graders in learning from single text. In Experiment 1, seventh graders read two complementary texts either massed or distributed by a lag of one week between the texts. Learning outcomes were measured immediately after reading the second text and one week later. Judgements of learning were assessed immediately after each text. Experiment 2 replicated the paradigm of Experiment 1 while shortening the lag between the texts in the distributed condition to 15 min. In both experiments, an interaction effect between learning condition (distributed vs. massed) and retention interval (immediate vs. delayed) was found. In the distributed condition, the participants showed no decrease in performance between the two tests, whereas participants in the massed condition did. However, no beneficial effects were found in the delayed test for the distributed condition but even detrimental effects for the distributed condition in the immediate test. In Experiment 1, participants in the distributed condition perceived learning as less difficult but predicted lower success than the participants in the massed condition. Experiment 3 replicated the paradigm of Experiment 1 with university students in the laboratory. In the preregistered Experiment 4, an additional retention interval of two weeks was realized. In both experiments, the same interaction between learning condition and retention interval was found. In Experiment 3, the participants in the distributed condition again showed no decrease in performance between the two tests, whereas participants in the massed condition did. However, even at the longer retention interval in Experiment 4, no beneficial effects were found for the distributed condition. Domain-specific prior knowledge was positively associated with test performance in both experiments. In Experiment 4, the participants with low prior knowledge seemed to be impaired by distributed learning, whereas no difference was found for participants with medium or high prior knowledge. In the preregistered Experiment 5, seventh graders read a single text twice. The rereading took place either massed or distributed with one week. Immediately after rereading, judgements of learning were assessed. Learning outcomes were assessed four min after second reading or one week later. Participants in the distributed condition predicted lower learning success than participants in the massed condition. An interaction effect between learning condition and retention interval was found, but no advantage for the distributed condition. Participants with low domain-specific prior knowledge showed lower performance in short-answer questions in the distributed condition than in the massed condition. Overall, the results seem less encouraging regarding the effectiveness of distribution on learning from single and multiple texts. However, the experiments reported here can be perceived as first step in the realistic investigation of distribution in learning from texts.},
  subject      = {Textverstehen},
  language  = {en}
}
@article{GrevingRichter2021,
  author    = {Greving, Carla Elisabeth and Richter, Tobias},
  title     = {Beyond the Distributed Practice Effect: Is Distributed Learning Also Effective for Learning With Non-repeated Text Materials?},
  series = {Frontiers in Psychology},
  volume    = {12},
  journal   = {Frontiers in Psychology},
  issn      = {1664-1078},
  doi       = {10.3389/fpsyg.2021.685245},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-247944},
  year      = {2021},
  abstract  = {Distributed learning is often recommended as a general learning strategy, but previous research has established its benefits mainly for learning with repeated materials. In two experiments, we investigated distributed learning with complementary text materials. 77 (Experiment 1) and 130 (Experiment 2) seventh graders read two texts, massed vs. distributed, by 1 week (Experiment 1) or 15 min (Experiment 2). Learning outcomes were measured immediately and 1 week later and metacognitive judgments of learning were assessed. In Experiment 1, distributed learning was perceived as more difficult than massed learning. In both experiments, massed learning led to better outcomes immediately after learning but learning outcomes were lower after 1 week. No such decrease occurred for distributed learning, yielding similar outcomes for massed and distributed learning after 1 week. In sum, no benefits of distributed learning vs. massed learning were found, but distributed learning might lower the decrease in learning outcomes over time.},
  language  = {en}
}