Symposium
Benefits of generative learning activities for creating lasting knowledge
Chair(s): Veit Kubik (University of Würzburg), Mirjam Ebersbach (University of Kassel), Tobias Richter (University of Würzburg)
Discussant(s): Lennart Schalk (Schwyz University of Teacher Education)
A major goal of education is to create and foster lasting knowledge. To this end, the field of learning and instruction investigates conditions and interventions that enable learners to acquire knowledge they can access over a long time and use flexibly when needed. However, empirical research in psychology and education has focused almost exclusively on relatively short periods of time and often on memory performance as the preferred learning outcome, leaving a research gap on how to obtain durable and general benefits of learning and instructional techniques.
Prior research, specifically on instructional design, has highlighted the usefulness of generative activities that serve both knowledge elaboration and consolidation (Fiorella & Mayer, 2016) and in turn long-term and transfer-oriented learning. In particular, when combined with retrieval practice, generative learning tasks provide the instructional support that students often need to elaborate and consolidate the learned contents. For example, typical generative learning tasks prompt students to self-explain, write learning protocols (Nückles et al., 2020), explain the learned contents to fictitious others (i.e., Fiorella & Mayer, 2013), or create external visual representations such as drawings (Ainsworth & Scheiter, 2021). These generative learning tasks can help to build up coherent mental representations of new knowledge and to integrate it with learners’ prior knowledge (Roelle et al., 2023).
Against this background, the symposium will examine how generative learning (e.g., writing learning protocols, self-explanations, or generating a drawing) can be effectively implemented and also combined with practice in learning and instruction at both school and university levels to enhance long-lasting learning. Contribution 1 examines whether learning protocols are an effective instructional measure in the context of a follow-up course activity within a digital lecture among teacher university students. Specifically, the authors investigated the potential benefits of cognitive and metacognitive prompts, compared to a general prompt, as instructional support after 1 week in this unsupervised learning environment on both learning strategy use and comprehension performance. Contribution 2 examines the effectiveness of generating drawings as a generative learning strategy after 8 weeks in secondary school classrooms. Applying a pre-post-test experimental design, the authors compared explaining (to a fictitious peer) to restudy and examined the additive benefits of generating a drawing (explaining+drawing) or having access to an additional visualization (explaining+picture) for inquiry learning of physics contents. Contribution 3 investigates the effectiveness of combining self-explanation as a generative learning activity and retrieval practice as a desirable difficulty in the classroom of secondary education; the degree of retrieval practice was manipulated by implementing the retrieval task in a closed-book (vs. open-book) format. In two studies, the authors examined whether and how constructive retrieval (combined retrieval practice and self-explanation) benefits comprehension, retention, and future learning of complex physics content after 1 week and 12 weeks, compared to providing the two learning activities alone.
All contributions are based on sound experimental designs, measures of learning outcome at longer delays, and target partly different generative learning activities in different student populations, in part with integrating or measuring retrieval-practice activities. Taken together, these studies provide complementary perspectives on how to create lasting and flexible knowledge in school and university contexts. The three contributions will be discussed by an expert in the field of teaching methods, learning materials, and instructional design in learning. The expert’s views on the presented research will contribute to draw theoretical and practical conclusions on how to combine and integrate generative learning principles and desirable difficulties to enhance long-term learning and transfer of knowledge to the (high-)school context and more complex learning materials. These educationally relevant findings will provide an important basis for evidence-based decisions in educational practice and policy (Kultusministerkonferenz, 2015; Slavin, 2002).
Presentations of the Symposium
Learning protocols in a digital lecture: Cognitive, but not metacognitive prompts enhance comprehension and transfer
Veit Kubik1, Markus H. Hefter2, Matthias Nückles3, Kirsten Berthold2
1University of Würzburg, 2Bielefeld University, 3Matthias Nückles, University of Freiburg
Background
Writing learning protocols can foster generative learning (Roelle et al., 2023). One prominent way to enhance the effectiveness of learning protocols is to provide explicit prompts for students to apply cognitive and metacognitive strategies (Nückles et al., 2020). However, prior studies were typically conducted in a traditional, lab-based setting that provides strict experimental control (Berthold et al., 2007; Nückles et al., 2009). In recent years, COVID-19 policy measures required lecturers to provide prerecorded lectures in a digital format and students to learn the lecture’s contents in a self-regulated fashion largely at home. Prompted learning protocols may not be as instructionally supportive in this unsupervised digital environment. For example, given the increased risks of interruptions and students’ lower engagement, the learning protocol quality may decrease and with it the learning outcome. The aim of this study was to investigate how effective cognitive and metacognitive prompts are when provided in learning protocols as unsupervised follow-up course work within a digital lecture.
Hypotheses
(1) Cognitive prompts foster the application of organization and elaboration strategies, and metacognitive prompts foster the application of metacognitive strategies.
(2) We tested the following hypotheses on the learning outcome.
- Cognitive prompts lead to higher learning outcomes than a general prompt, and this cognitive prompt benefit is mediated by students’ use of organization and elaboration learning strategies.
- Metacognitive prompts lead to higher learning outcomes than a general prompt. This predicted benefit of metacognitive prompts will be mediated by students’ use of metacognitive strategies.
Methods
We conducted an experimental field study during an online lecture. After a self-paced pretest, N = 97 student teachers watched a video lecture about Piaget and his Theory of Cognitive Development. In the second phase, they were instructed to write a learning protocol (30 min) and were randomly assigned to three experimental groups in which they received additional prompt(s) as instructional support: metacognitive prompts, cognitive prompts, versus a general prompt. In the third phase, student teachers provided with the lecture’s transcript to revise their learning protocols (30 min). In the final phase, they took a posttest after 1 week.
Preliminary Results
As compared to a general prompt, cognitive prompts specifically enhanced the students’ application of elaboration and organization strategies, while metacognitive prompts elicited the use of metacognitive strategies (ps < 0.05). Importantly, a one-factorial ANOVA on the overall posttest score revealed a significant main effect, F(2, 91) = 7.08, p < .001, ƞp2 = .135. A-priori contrast analyses showed that cognitive prompts, t = 3.57, p < .001, but not metacognitive prompts, t = 0.80, p = .425, lead to a higher learning outcome as compared to a general prompt. In addition, cognitive prompts resulted in a significant higher posttest performance than metacognitive prompts, t = 2.73, p = .008. This results pattern was existent for both comprehension and transfer performance, but there was no significant difference between experimental groups on retention, ps > .360. The benefit of cognitive prompts, compared to a general prompt, was fully mediated by the frequency of students’ use of elaboration strategies (β = .200, 95% CI [0.049, 3.746]).
Discussion
The results supported our hypothesis that cognitive and metacognitive prompts fostered the application of the learning strategies. Cognitive prompts resulted in higher comprehension and transfer but not higher retention performance. These findings suggest that prompts help to enhance the representations’ quality and elaboration rather than its consolidation (Nückles et al., 2020). The beneficial effects of cognitive prompts were related to students’ use of elaboration strategies. Similar to the results by Berthold et al. (2007), metacognitive prompts were not effective, despite the opportunity to revise the learning protocol–a finding that may be attributed to students’ low engagement in metacognitive strategies.
Fostering lasting learning from inquiry with non-interactive generative activities: Explaining and drawing matter
Heike Russ1, Leonie Sibley1, Salome Flegr2, Jochen Kuhn3, Vincent Hoogerheide4, Katharina Scheiter5, Andreas Lachner1
1Eberhard Karls University of Tübingen, 2Eberhard Karls University of Tübingen, Ludwig-Maximilians-University of Munich, 3Ludwig-Maximilians-University of Munich, 4University of Utrecht, 5University of Potsdam
Constructing elaborated and lasting knowledge is a crucial endeavor in inquiry-based learning in school (Pedaste et al., 2015). However, school performance studies such as PISA or TIMSS attested to German students’ comparatively low achievements, especially in terms of scientific literacy or science achievements. To foster these achievements and associated lasting learning, effective instructional strategies are required. In this regard, empirical research indicated that pure learning from inquiry often puts high cognitive demands on school students, which precludes the envisioned benefits regarding lasting knowledge acquisition. Therefore, students need support with the elaborating and consolidation processes involved, to which generative activities are regarded to contribute (Fiorella & Mayer, 2016). Generative learning comprises different activities, such as creating verbal representations when explaining the learned contents to fictitious others (i.e., Fiorella & Mayer, 2013) or creating external visual representations like drawings (Ainsworth & Scheiter, 2021). How combinations of these multiple representations should be orchestrated to foster inquiry and lasting learning in school, is still an open question.
In this study, we aimed to close this research gap and combined non-interactive explaining with drawing in an authentic classroom setting with secondary school students (7th and 8th grade, N = 590), focusing inquiry learning about the topic of converging lenses (physics, geometrical optics). We applied a pre-posttest experimental design, including an immediate and an eight-week delayed posttest, and four conditions: students either explained the learned contents to a fictitious peer (explaining), explained with having access to an additional visualization of the contents (explaining+picture), or explained with generating a drawing (explaining+drawing). A control group restudied the materials. We stated the following hypotheses: First, explaining (i.e., explaining, explaining+picture, explaining+drawing) should be more beneficial than restudy. Second, the combined visualization conditions (i.e., explaining+picture, explaining+drawing) should be more effective than the explaining condition. Third, explaining and actively generating a drawing (i.e., explaining+drawing) would be more beneficial than explaining with a provided picture. We assumed that the effects of our interventions would be more pronounced in the delayed posttest than in the immediate posttest. To answer our research questions, we performed planned contrast analyses.
Results revealed that students who explained outperformed students in the control condition regarding their immediate learning outcome (d = .06, p = .006). Regarding monitoring accuracy, the control group judged their knowledge more accurately than the explaining conditions (d = -.06, p = .011). There were no significant differences in the immediate learning outcome (d = -.06, p = .068) and monitoring accuracy (d = -.05, p = .128) between the combined visualization conditions and the explaining condition. As expected, students who explained and generated a drawing outperformed students who explained with a provided picture regarding their immediate learning outcome (d = .12, p = .032). However, there were no differences in immediate monitoring accuracy (d = -.03, p = .566). Overall, there were no differences in delayed learning outcomes and monitoring accuracy.
The findings highlight the crucial role of combining explaining with drawing tasks to enhance students’ mental representations during inquiry learning. However, the activities did not result in lasting learning. Further research is needed to explore how generative activities can be combined with consolidation activities, for instance, by inducing desirable difficulties (Richter et al., 2022), to fully enable lasting learning.
Constructive retrieval with complex learning contents – Does the combination of self-explanation and closed-book improve lasting learning and preparation for future learning?
Alexander Renkl1, Tino Endres1, Johanna Bohm1, Andreas Vorholzer2, Alexander Eitel3, Claudia von Aufschnaiter3
1University of Freiburg, 2Technical University of Munich, 3Justus-Liebig-University Giessen
Theoretical Background and Research Question
Learning in school involves two key instructional goals: (1) Comprehension: Students need to comprehend the learning content to be able to apply their knowledge to new and more complex contexts (Roelle et al., 2022). One way to promote comprehension, is to prompt generative learning activities such as (principle-based) self-explanations that lead to more elaborate processing (Renkl & Eitel, 2019). (2) Consolidation and future learning: In school, learning content often builds on each other (cumulative curriculum). Students therefore have to retrieve previously acquired knowledge after longer delays to expand their knowledge based on it. One way to support knowledge consolidation are desirable difficulties such as retrieval practice. Retrieval practice tasks require students to retrieve previously learned information from memory, thereby consolidating the respective content (Pan & Rickard, 2018). To investigate retrieval practice effects in the classroom, open-book tasks (students can look up information) and closed-book task (students have to retrieve / cannot look up information) can be used. Because students have to retrieve task-relevant information, closed-book tasks increase retrieval demands and thus improve learning (Rummer, 2019).
These studies investigate if and how combining retrieval practice and generative learning activities (e.g., self-explanations) – also known as constructive retrieval (Hinze et al., 2013) – promotes comprehension and consolidation of complex learning contents in physics, resulting in lasting learning.
Study 1
Method: As part of their regular physics lessons, students (11th grade; N = 120) learned about the topic of mechanics (linear movements) in a multimedia learning environment. All learning tasks within the learning environment were presented in closed-book format, creating high retrieval demands. Students were randomly assigned to one of two conditions (self-explanation vs. description prompts) and participated in three sessions: (1) Demographic data, pre-test (comprehension) and working on the learning environment; (2) one-week delayed posttest (retention, comprehension); (3) twelve-weeks delayed posttest (comprehension) and assessment of students’ preparation for future learning. To measure future learning and transfer, students worked on a multimedia instruction on circular motion that thematically builds upon the first learning environment. As a crucial influence on the success of constructive retrieval, task performance within the first learning environment is coded in terms of self-explanatory quality and retrieval success (Roelle et al., 2023).
Results: The analysis of the pre-test and post-test considers item response theory. Regarding comprehension, an ANOVA with 3 repeated measures reveals that additionally to an overall learning gain for all students, the learning gain in the self-explanation prompt condition after one week was higher than in the description prompt condition, F(1,101) = 4.276, p < .05, ƞp2 = .04. As compared to the pre-test, there is a tendency towards the latter effect even after 12 weeks, F(1,101) = 3.774, p = .055, ƞp2 = .04.
Discussion: The first study’s results show that constructive retrieval enhances long-term learning in complex physics content. In the subsequent study, we aim to explore how varying retrieval demands impact those benefits.
Study 2
In addition to the learning activity (self-explanation vs. description prompts), we vary retrieval demands (closed-book vs. open-book). Otherwise, the procedure is identical to Study 1. We will test the effects of constructive retrieval using a 2 x 2 analysis comparing lasting learning and preparation for future learning. A mediation analysis will examine mental effort and self-explanation quality as mediators. Data collection will be completed in January 2024. Thus, we will present first results and discuss implications in March.
General Discussion
Both studies will illuminate whether constructive retrieval is useful with complex knowledge structures as in physics. By investigating constructive retrieval in an authentic classroom setting, we can assess the pivotal role of construction and retrieval within cumulative curricula.
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