Generative Learning: Which Strategies for What Age?

Abstract

Generative learning strategies are intended to improve students’ learning by prompting them to actively make sense of the material to be learned. But are they effective for all students? This review provides an overview of six popular generative learning strategies: concept mapping, explaining, predicting, questioning, testing, and drawing. Its main purpose is to review for what ages the effectiveness of these strategies has been demonstrated and whether there are indications of age-related differences in their effectiveness. The description of each strategy covers (1) how it is supposed to work, (2) the evidence on its effectiveness in different age groups, and (3) if there are age-related differences in its effectiveness. It is found that while all six generative learning strategies reviewed have proven effective for university students, evidence is mixed for younger students. Whereas some strategies (practice testing, predicting) seem to be effective already in lower-elementary-school children, others (drawing, questioning) seem to be largely ineffective until secondary school. The review closes with a call for research on the cognitive and metacognitive prerequisites of generative learning that can explain these differences.

Does increasing social presence enhance the effectiveness of writing explanations?

“…The null findings regarding students' comprehension might be attributed to low levels of prior knowledge. Little prior knowledge limits students in learning new contents adequately [30,84]. However, prior research revealed that generative learning activities, such as explaining, are in particular beneficial for low prior knowledge students [9].…”

“…Then, they need to connect the new contents with their already existing knowledge to integrate them into their long-term memory [27,29,30]. Through this connection, students are able to provide explanations that include further details and information that go beyond the giving materials, which results in new knowledge and meaningful learning [27][28][29][30][31][32][33][34]. This process additionally triggers students to monitor whether they understood all relevant contents correctly or whether they need to restudy specific information.…”

How Can We Make Active Learning Work in K–12 Education? Considering Prerequisites for a Successful Construction of Understanding

“…From a psychological perspective, we are talking about the effects of (a) agency beliefs, (b) prior-knowledge activation, (c) cognitive capacities for sense making, and (d) metacognitive capacities for self-reflection. As briefly summarized in the next section, all of these psychological constructs have been intensively researched, and their developmental trajectory is well known (for a more detailed account, see Brod, 2020). This summary provides the basis for the quintessence of this commentary, which is that knowledge of developmental trajectories and the effects they have on learning can guide our understanding of how to make active-learning practices work in K–12 education and beyond.…”

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“…In line with the generative learning theory, the process of explaining as a generative act may elicit cognitive (e.g., mental effort) and metacognitive (e.g., monitoring) processes, which should contribute to students' comprehension: First, and in line with Mayer's SOI model [28], when explaining students need to select the most relevant information if the provided materials and to organize the information in a coherent way. Then, they need to connect the new contents with their already existing knowledge to integrate them into their long-term memory [27,29,30]. Through this connection, students are able to provide explanations that include further details and information that go beyond the giving materials, which results in new knowledge and meaningful learning [27][28][29][30][31][32][33][34].…”

“…Additionally, results indicated a higher correlation between prior knowledge and students' learning outcome, suggesting that the provided learning material was too difficult, which may explain the null findings. Seemingly, students have problems in applying this learning strategy successfully when the learning material is overly difficult [30], which highlights the need for additional support during learning, such as pre-trainings or prompts [39,43,95].…”