Dragan Trninic

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Trninic

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Dragan

ORCID

0000-0002-5948-2441

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Publications 1 - 10 of 21

Synchronous Brain Activities in Mathematical Task Processing
Tobler, Samuel; Poikonen, Hanna; Gashaj, Venera; et al. (2023)
Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023
Differential benefits of explicit failure-driven and success-driven scaffolding in problem-solving prior to instruction
Sinha, Tanmay; Kapur, Manu; West, Robert; et al. (2021)
Journal of Educational Psychology
Unscaffolded problem-solving before receiving instruction can give students opportunities to entertain their exploratory hypotheses at the expense of experiencing initial failures. Prior literature has argued for the efficacy of such preparatory activities in preparing students to learn from instruction. Despite growing understanding of the underlying cognitive mechanisms, the pedagogical value of success or failure in initial problem-solving attempts is still unclear. We do not know yet whether some ways of succeeding or failing are more efficacious than others. We report empirical evidence from a classroom intervention (N = 221), where we designed scaffolds to explicitly push student problem-solving toward success via structuring, but also toward failure via problematizing. Our rationale for explicit failure scaffolding was rooted in facilitating problem-space exploration. We subsequently compared the differential preparatory effects of success-driven and failure-driven problem-solving on learning from follow-up instruction. Results suggested that failure-driven scaffolding (nudging students to generate suboptimal solutions) and success-driven scaffolding (nudging students to generate optimal solutions by giving them heuristics with low specificity) had similar outcomes on posttest assessments of conceptual understanding. Students exposed to failure-driven scaffolding, however, demonstrated higher quality of constructive reasoning. These trends were more salient for the learning concept with greater difficulty. (PsycInfo Database Record (c) 2021 APA, all rights reserved)
Math on cortex – Underlying delta synchrony during naturalistic math demonstrations in math experts and novices
Poikonen, Hanna; Tobler, Samuel; Trninic, Dragan; et al. (2022)
Proceedings of the 16th International Conference of the Learning Sciences - ICLS 2022
Neuroimaging studies show that expertise in math shapes brain functions. To understand the brain processes behind complex math tasks and manipulation of large abstract concepts, we need to study the brain with naturalistic stimuli. Such stimuli are, for example, long math demonstrations that evoke simultaneous and overlapping cognitive and metacognitive processes. In our EEG study, we compared math experts and novices while they actively processed long math demonstrations in sitting and standing. Experts had an enhanced delta (0.5-4 Hz) phase synchrony over the centro-parieto-occipital electrodes compared to novices. Internal concentration and engagement may play a role in such enhanced delta synchrony.
The Neural and Physiological Mechanisms of Learning through Productive Failure
Formaz, Cléa; Hoffmann, Sven; Gashaj, Venera; et al. (2021)
EARLI 2021 online book of abstracts.
Productive Failure is a learning design that creates conditions for learners to persist in generating and exploring representations and solution methods for solving complex, novel problems prior to formal instruction. There is a growing body of evidence that problem-solving followed by instruction can lead to better conceptual understanding and knowledge transfer, compared to instruction followed by problem-solving. This learning advantage occurs even in the face of initial failure to solve the problem. Research on productive failure yielded a number of cognitive mechanisms for why students learn better after encountering difficulties; however, the physiological mechanisms underpinning this process have yet to be explored. Recent research suggests a connection between heartbeats and cognitive processes, offering a novel method for investigating the physiological mechanisms of learning. Here, we introduce a novel means to explore the physiological mechanisms underlying the process of learning from failure, and argue for its usefulness. In particular, we aim to build a deeper explanatory basis of productive failure by exploring the impact of different heartbeat measurements and corroborating these measurements with behavioral signatures.
Bridging the Theory and Empiry of Failure
Nardo, Aline; Trninic, Dragan (2020)
Philosophy of Education
Math on cortex—enhanced delta phase synchrony in math experts during long and complex math demonstrations
Poikonen, Hanna; Tobler, Samuel; Trninic, Dragan; et al. (2024)
Cerebral Cortex
Neural oscillations are important for working memory and reasoning and they are modulated during cognitively challenging tasks, like mathematics. Previous work has examined local cortical synchrony on theta (4–8 Hz) and alpha (8–13 Hz) bands over frontal and parietal electrodes during short mathematical tasks when sitting. However, it is unknown whether processing of long and complex math stimuli evokes inter-regional functional connectivity. We recorded cortical activity with EEG while math experts and novices watched long (13–68 seconds) and complex (bachelor-level) math demonstrations when sitting and standing. Fronto-parietal connectivity over the left hemisphere was stronger in math experts than novices reflected by enhanced delta (0.5–4 Hz) phase synchrony in experts. Processing of complex math tasks when standing extended the difference to right hemisphere, suggesting that other cognitive processes, such as maintenance of body balance when standing, may interfere with novice’s internal concentration required during complex math tasks more than in experts. There were no groups differences in phase synchrony over theta or alpha frequencies. These results suggest that low-frequency oscillations modulate inter-regional connectivity during long and complex mathematical cognition and demonstrate one way in which the brain functions of math experts differ from those of novices: through enhanced fronto-parietal functional connectivity.
Problem‑solving before instruction for learning linearalgebra in university mathematics
Baumgartner, Vera; Daguati, Simona; Trninic, Dragan; et al. (2025)
Instructional Science
Problem-solving before instruction has been shown to be a more effective learning design than traditional tell-and-practice for several mathematical concepts at the secondary school level. In particular, the more a problem-solving before instruction design follows the productive failure principles, such as comparing and contrasting student-generated solutions, the higher the effect on students’ conceptual understanding and transfer. University mathematics education poses several inherent constraints that complicate the implementation of these principles. In the present study, we implemented a problem-solving before instruction design in a university linear algebra course adhering to the productive failure principles as closely as possible. Participation in the preparatory problems was voluntary. We investigated the effect on students’ learning over four one-year iterations in a design-based research approach. Compared to the baseline (aggregate of cohorts prior to the intervention), we observed a significant increase in final exam performance for all four cohorts with effect sizes between Cohen’s d = 0.28 and d = 0.59. For students who agreed to further analyses, our results show that up to 16% of the variance in students’ performance can be explained by variance in their participation in the problem-solving before instruction design. As our design did not include a control group, we refrain from conclusions regarding any design components that might have caused these effects. However, these results are promising, given that our implementation involved only minor changes to the original course structure and required little extra time for students.
The AL Goldberg machine: a virtual environment for engaging learners in algorithmic practices
Pearl, Harrison; Arrants, Samuel; Swanson, Hillary; et al. (2020)
Proceedings of the 2020 ACM Interaction Design and Children Conference: Extended Abstracts: IDC '20
Familiarity with the construction, test, and refinement of computational algorithms is of critical importance to many disciplines in the 21st century. We introduce a novel learning environment that lowers the threshold to participation in algorithmic practices including using functions to transform input, using conditionals to selectively transform or manipulate input, creating simple and complex algorithms, and testing and debugging algorithms to iteratively improve them. Our learning environment leverages VR technology and principles of embodied cognition that prioritize "hands in" learning. Instead of creating algorithms through traditional computational programming (which often renders the structure and components of an algorithm opaque), students using our technology build "concrete algorithms" in the form of a virtual Rube Goldberg-type machine that makes the algorithm's structure, components, and functioning visible.
Comparing the effectiveness of preparatory activities that help undergraduate students learn from instruction
Trninic, Dragan; Sinha, Tanmay; Kapur, Manu (2022)
Learning and Instruction
Students can learn better from instruction after first engaging in activities that prepare them to learn (Kapur, 2016; Loibl, Roll, & Rummel, 2017; Schwartz & Bransford, 1998). In this study, we compare the effectiveness of four activities that prepare university students to learn from instruction. We use productive failure, an established instructional design, as the baseline preparatory condition. In productive failure, students generate solutions to challenging but accessible problems, which serves as preparation for formal instruction. We compare this approach with three alternative preparatory activities: contrasting a correct and an incorrect solution, sensemaking of the correct solution only, and studying a fully worked-out example of the correct solution. Despite the differences in preparatory activities, participants on average performed nearly identically on most of the process and outcome measures. In universities, or with similarly advanced learners, a variety of activities may be equally effective at preparing students to learn from instruction.
The Disappearing “Advantages of Abstract Examples in Learning Math”
Trninic, Dragan; Kapur, Manu; Sinha, Tanmay (2019)
Proceedings of the 41st Annual Conference of the Cognitive Science Society

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