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Apr 26, 2023 · How do learners make sense of what they are learning? In this article, I present a new framework of sense-making based on research investigating the benefits and boundaries of generative learning activities (GLAs). The generative sense-making framework distinguishes among three primary sense-making modes—explaining, visualizing, and enacting—that each serve unique and complementary ...
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Generative learning involves actively making sense of to-be-learned information by mentally reorganizing and integrating it with one’s prior knowledge, thereby enabling learners to apply what they have learned to new situations. In this article, we present eight learning strategies intended to promote generative learning: summarizing, mapping, drawing, imagining, self-testing, self ...
- Logan Fiorella, Richard E. Mayer
- 2016
- Generating Concept Maps
- Generating Explanations
- Generating Predictions
- Generating Questions
- Generating Answers
- Generating Drawings
- Overall Summary
How Is it Supposed to Work?
Concept maps depict the hierarchy of and relations among concepts (for a toy example of a concept map, see Fig. 1). This technique is based on Ausubel’s (1960) assimilation theory of cognitive learning and was developed by Novak and colleagues as an instructional tool to represent knowledge structures and to promote meaningful learning (e.g., Novak 1990). According to Ausubel, meaningful learning can be achieved by anchoring new ideas or concepts with previously acquired knowledge. Concept ma...
For What Ages Has Its Effectiveness Been Demonstrated?
Several reviews and meta-analyses indicate that generating concept maps is generally beneficial for learning (e.g., Horton et al. 1993; Nesbit and Adesope 2006; Novak 1990). The most recent and comprehensive meta-analysis by Schroeder et al. (2018), which clearly distinguished self-generated and provided concept maps, revealed that the mean size of the effect of self-generated concept mapping on students’ achievement scores was 0.72 SDs. As can be expected, this beneficial effect was greater...
Are There Age-Related Differences in Its Effectiveness?
Concept maps can be implemented in various ways and with varying instructional support, which may impact their effectiveness in different age groups. Direct evidence for this idea has been provided in a study comparing concept mapping among college and high-school students, which revealed a map coherence × age group interaction (Gurlitt and Renkl 2008). University students profited more when they received a low-coherence map that required them to create and label lines and thus called for mor...
How Is It Supposed to Work?
Researchers have suggested that asking students to generate explanations during learning activates relevant prior knowledge and facilitates integration and organization of new information (Chi et al. 1994; Pressley et al. 1992; Renkl et al. 1998). This strategy further encourages elaboration of the new information, such as processing similarities and differences among elements of the to-be-learned content (Dunlosky et al. 2013). Such processing has been shown to be beneficial for memory (Hunt...
For What Ages Has Its Effectiveness Been Demonstrated?
Beneficial effects of both elaborative interrogation and self-explanation have been reported for various student groups and under various learning conditions (for an overview, see Dunlosky et al. 2013). A recent meta-analysis on self-explanation (Bisra et al. 2018) that did not include unpublished studies revealed a mean effect size of 0.55 SDs when conditions in which participants were instructed to explain content to themselves were compared with conditions in which they were not instructed...
Are There Age-Related Differences in Its Effectiveness?
Because generating an explanation for novel phenomena requires at least some reasoning abilities, it could be expected to disadvantage younger students. In short, it is not before around age 9 that children are consistently able to generate inferences based on deep structural similarity (Gentner and Toupin 1986), and this inability should hamper their ability to generate explanations based on underlying properties of to-be-learned material. However, laboratory experiments with children as you...
How Is It Supposed to Work?
In this technique, teachers ask learners to generate a prediction (often called hypothesizing in science classes) about a specific fact or outcome before providing them with the to-be-learned information. Generating a prediction requires accessing prior knowledge and connecting it to the new information being learned (Schmidt et al. 1989). Furthermore, generating a prediction may stimulate curiosity for the correct answer (Brod and Breitwieser 2019; Potts et al. 2019) and if the correct answe...
For What Ages Has Its Effectiveness Been Demonstrated?
Asking students to generate predictions has been successful in classroom studies that have investigated ways to improve students’ learning in various fields of study, including learning from text (Fielding et al. 1990; Palinscar and Brown 1984), physics (Champagne et al. 1982; Inagaki and Hatano 1977; Liew and Treagust 1995), and biology (Schmidt et al. 1989). In addition, asking students to generate predictions is a component of teaching with audience response systems, which have been shown...
Are There Age-Related Differences in Its Effectiveness?
Metcalfe and Kornell (2007) compared sixth-graders and college students on a definition-learning task in which children had to generate (mostly incorrect) definitions before seeing the correct one. Similarly for both age groups, this prediction condition yielded better learning than control conditions in which the correct definition was presented at the same time as the word or in which no correct definition was presented (i.e., no feedback on the correctness of the prediction). A recent stud...
How Is It Supposed to Work?
Asking a good question requires accessing and elaborating relevant prior knowledge, and a key instructional goal of this technique is to help learners identify gaps in their knowledge (for overviews, see Graesser et al. 1992; King 1992). This technique can be implemented either in an interactive context, such as in reciprocal teaching (Palinscar and Brown 1984) or guided questioning of peers (King 1994), or in the form of questioning oneself (Wong 1985). For the purpose of this review, only t...
For What Ages Has Its Effectiveness Been Demonstrated?
The overwhelming majority of studies on question generation have been carried out in the domain of text comprehension. A review of studies that examined the effects of generating questions in this domain (Wong 1985) indicated that generating questions had a beneficial effect if students were properly instructed on how to do it beforehand and if they were given sufficient time to do so. A meta-analysis of intervention studies in which students were first taught to generate questions either dur...
Are There Age-Related Differences in Its Effectiveness?
The evidence discussed in the last section already strongly suggests the existence of age-related differences in the effectiveness of generating questions. One study has examined age-related differences in the effectiveness of student-generated questions directly (Denner and Rickards 1987). It compared text comprehension in fifth-, eighth-, and eleventh-graders and found that self-generated questions were less effective than provided questions and not more effective than rereading in promotin...
How Is It Supposed to Work?
Answering test questions about previously learned material is known by many names—most prominently, self-testing, practice testing, and retrieval practice. The focus on practice makes clear that this method qualifies as a GLS because it is not intended as a one-shot summative assessment of learners’ knowledge but rather involves repeated activity to enhance their retention of the material (Fiorella and Mayer 2016). According to the rationale for this strategy, attempting to retrieve target in...
For What Ages Has Its Effectiveness Been Demonstrated?
In the past two decades, a plethora of studies have found a strong beneficial effect of practice testing on learning (also called the testing effect, for reviews, see Rawson and Dunlosky 2012; Roediger and Butler 2011). A meta-analysis (Rowland 2014) that took into account unpublished studies revealed a moderately strong effect size (0.50 SDs) for studies that compared testing with a restudy control condition. Another meta-analysis that also included no-activity control conditions revealed sl...
Are There Age-Related Differences in Its Effectiveness?
Turning to studies that compared different age groups, Lipowski et al. (2014) tested first- and third-graders and found robust beneficial effects of testing compared with restudying. While the benefit of testing compared with restudying was stronger in third-graders than in first-graders, the interaction did not reach significance. A significant interaction between age and condition (testing, restudying) was found in a study that compared lower elementary, upper elementary, and college studen...
How Is It Supposed to Work?
Asking learners to draw an illustration that looks like or corresponds to a studied concept has been investigated mainly in the context of learning from instructional texts (but see Ploetzner and Fillisch 2017). To draw an illustration, learners have to translate the verbal information into a picture that represents spatial relationships among the elements mentioned in the text (Alesandrini 1984; Schwamborn et al. 2010). Drawings are different from concept maps in that the latter do not physi...
For What Ages Has Its Effectiveness Been Demonstrated?
Research has by and large revealed positive effects of learner-generated drawing, but findings have been inconsistent (for reviews, see Alesandrini 1984; Leutner and Schmeck 2014; Van Meter and Garner 2005). A recent review/meta-analysis (Fiorella and Zhang 2018) that included only published studies revealed that drawing was clearly more effective than just reading a text for both text comprehension (0.46 SDs) and transfer performance (0.75 SDs). However, when compared to provided illustratio...
Are There Age-Related Differences in Its Effectiveness?
While the evidence discussed in the last section already strongly suggests the existence of age-related differences, two studies directly compared the effectiveness of generating drawings between different age groups. One (Van Meter et al. 2006) compared fourth- and sixth-graders in a design similar to that of Van Meter (2001), including a read-only condition as well as three drawing conditions that varied in instructional support. Gains in conceptual knowledge were assessed on a problem-solv...
The first and foremost goal of this review was to evaluate the evidence for the effectiveness of six popular GLSs in improving declarative learning in different age groups. All six techniques reviewed generally work well for university students, which should make them promising for younger students as well. The success of these techniques with univ...
- Garvin Brod, Garvin Brod
- garvin.brod@dipf.de
- 2021
Aug 29, 2023 · In the ever-evolving era of technological advancements, generative artificial intelligence (GAI) emerges as a transformative force, revolutionizing education. This review paper, guided by the PRISMA framework, presents a comprehensive analysis of GAI in education, synthesizing key insights from a selection of 207 research papers to identify research gaps and future directions in the field.
3 days ago · Sixty three percent (n = 17) of respondents indicated they do not think the use of generative AI in teaching and learning could lead to a dehumanization of education. However, 70% (n = 19) indicated they were concerned that its use in learning and teaching could lead to students becoming overly reliant on technology.
May 6, 2024 · This paper explores the potential impact. of generative AI on future learning environments. Challenges include ensuring ethical use, maintaining authenticity, and addressing biases inherent in the ...
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May 7, 2024 · The recent emergence of generative AI (GenAI) tools such as ChatGPT, Midjourney, and Gemini have introduced revolutionary capabilities that are predicted to transform numerous facets of society fundamentally. In higher education (HE), the advent of GenAI presents a pivotal moment that may profoundly alter learning and teaching practices in aspects such as inaccuracy, bias, overreliance on ...
