Exploring Multiple Strategic Problem Solving Behaviors in Educational Psychology Research by Using Mixture Cognitive Diagnosis Model.
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ABSTRACT:
SUBMITTER: Zhang J
PROVIDER: S-EPMC8211444 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The primate prefrontal cortex (PF) plays a central role in choosing goals and strategies. To better understand its mechanisms, we recorded from PF neurons as monkeys used abstract response strategies to select a spatial goal. A visual cue, selected randomly from a set of three cues, appeared on each trial. All three cues were novel when neuronal recording commenced. From trial to trial, the cue could have either been repeated or changed from the previous trial; these were called repeat trials and change trials, respectively. On repeat trials, the monkeys used a Repeat-stay strategy to gain a reward by choosing the same spatial goal as on the previous trial; on change trials, they used a Change-shift strategy to reject the previous goal in favour of an alternative. We reported previously that when monkeys performed the task correctly, many PF neurons had activity encoding one of these two strategies. The monkeys sometimes chose the incorrect strategy, however. Strategy coding was weak or absent during the cue period of error trials which was, for correct trials, the time when the monkeys used a strategy to choose a future goal. By contrast, later in the trial, after the chosen goal had been attained and the monkeys awaited feedback, strategy coding was present and it reflected the strategy used, whether correct or incorrect. The weak cue-period strategy signal could, whatever its cause, have contributed to the errors made, whereas the activity prior to feedback suggests a role in monitoring task performance.
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Project description:In this paper we argue that a synthesis of findings across the various sub-areas of research in complex problem solving and consequently progress in theory building is hampered by an insufficient differentiation of complexity and difficulty. In the proposed framework of person, task, and situation (PTS), complexity is conceptualized as a quality that is determined by the cognitive demands that the characteristics of the task and the situation impose. Difficulty represents the quantifiable level of a person's success in dealing with such demands. We use the well-documented "semantic effect" as an exemplar for testing some of the conceptual assumptions derived from the PTS framework. We demonstrate how a differentiation between complexity and difficulty can help take beyond a potentially too narrowly defined psychometric perspective and subsequently gain a better understanding of the cognitive mechanisms behind this effect. In an empirical study a total of 240 university students were randomly allocated to one of four conditions. The four conditions resulted from contrasting the semanticity level of the variable labels used in the CPS system (high vs. low) and two instruction conditions for how to explore the CPS system's causal structure (starting with the assumption that all relationships between variables existed vs. starting with the assumption that none of the relationships existed). The variation in the instruction aimed at inducing knowledge acquisition processes of either (1) systematic elimination of presumptions, or (2) systematic compilation of a mental representation of the causal structure underpinning the system. Results indicate that (a) it is more complex to adopt a "blank slate" perspective under high semanticity as it requires processes of inhibiting prior assumptions, and (b) it seems more difficult to employ a systematic heuristic when testing against presumptions. In combination, situational characteristics, such as the semanticity of variable labels, have the potential to trigger qualitatively different tasks. Failing to differentiate between 'task' and 'situation' as independent sources of complexity and treating complexity and difficulty synonymously threaten the validity of performance scores obtained in CPS research.
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Project description:ObjectiveBarriers to medication adherence are common in pediatric epilepsy and associated with nonadherence, suboptimal seizure outcomes, and quality of life. A manualized, family-tailored education and problem-solving adherence intervention to address adherence barriers was tested in a randomized controlled trial in young children (2-12 years) with epilepsy. Study aims were to identify the adherence barriers and solutions chosen by families during intervention.MethodsParticipants with demonstrated non-adherence were randomized to either education attention control or treatment. In this exploratory, secondary analysis, treatment group data were examined, including adherence barriers and solutions discussed during face-to-face problem-solving sessions and telephone follow-ups. Treatment data were independently coded utilizing codebook thematic analysis.ResultsTwenty-seven children were randomized to treatment (M=7.5±2.9; 59.1% female). Across sessions, coding revealed 10 adherence barriers: Overall Forgetting (38-57%), Routine Change Routine (14-24%), Competing Activities (5-19%), Opposition (0-9%), Transition of Responsibility (0-5%), Running Out of Medication (0-10%), Forgetting During Travel (0-10%), Medication Not a Priority (0-5%), Medication Taste (0-5%), and Pill Swallowing (0-5%). Eight solution types were chosen and implemented by families: Environmental Cuing (29-50%), Multi-Pronged solutions (0-24%), Positive Reinforcement (14-23%), Back-up Doses (0-14%), Refill Tracking (0-10%), Caregiver Modeling of Adherence Behavior (0-5%), Pill Swallowing Intervention (0-5%), and Other (0-5%).ConclusionsResults highlight key adherence barriers identified by families of children with epilepsy and solutions implemented to address them. These data provide guidance to healthcare teams on how to successfully address adherence barriers in clinical settings.Clinical trials #NCT01851057.
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Project description:According to the restructuring hypothesis, insight problem solving typically progresses through consecutive stages of search, impasse, insight, and search again for someone, who solves the task. The order of these stages was determined through self-reports of problem solvers and has never been verified behaviorally. We asked whether individual analysis of problem solving attempts of participants revealed the same order of problem solving stages as defined by the theory and whether their subjective feelings corresponded to the problem solving stages they were in. Our participants tried to solve the Five-Square problem in an online task, while we recorded the time and trajectory of their stick movements. After the task they were asked about their feelings related to insight and some of them also had the possibility of reporting impasse while working on the task. We found that the majority of participants did not follow the classic four-stage model of insight, but had more complex sequences of problem solving stages, with search and impasse recurring several times. This means that the classic four-stage model is not sufficient to describe variability on the individual level. We revised the classic model and we provide a new model that can generate all sequences found. Solvers reported insight more often than non-solvers and non-solvers reported impasse more often than solvers, as expected; but participants did not report impasse more often during behaviorally defined impasse stages than during other stages. This shows that impasse reports might be unreliable indicators of impasse. Our study highlights the importance of individual analysis of problem solving behavior to verify insight theory.
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Project description:When confronted with novel problems, problem-solvers must decide whether to copy a modeled solution or to explore their own unique solutions. While past work has established that infants can learn to solve problems both through their own exploration and through imitation, little work has explored the factors that influence which of these approaches infants select to solve a given problem. Moreover, past work has treated imitation and exploration as qualitatively distinct, although these two possibilities may exist along a continuum. Here, we apply a program novel to developmental psychology (DeepLabCut) to archival data (Lucca et al., 2020) to investigate the influence of the effort and success of an adult's modeled solution, and infants' firsthand experience with failure, on infants' imitative versus exploratory problem-solving approaches. Our results reveal that tendencies toward exploration are relatively immune to the information from the adult model, but that exploration generally increased in response to firsthand experience with failure. In addition, we found that increases in maximum force and decreases in trying time were associated with greater exploration, and that exploration subsequently predicted problem-solving success on a new iteration of the task. Thus, our results demonstrate that infants increase exploration in response to failure and that exploration may operate in a larger motivational framework with force, trying time, and expectations of task success.
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Project description:Depression is a mental health condition for which individuals commonly seek treatment. However, depressive episodes often resolve on their own, even without treatment. One evolutionary perspective, the analytical rumination hypothesis (ARH), suggests that depression occurs in response to complex problems. According to this perspective, depressive symptoms promote analytical rumination, i.e., distraction-resistant thoughts about the causes of problems [causal analysis (CA)] and how they can be solved [problem-solving analysis (PSA)]. By helping individuals solve complex problems, analytical rumination may contribute to remission from depression. The aim of this study was to investigate (1) whether clinically-depressed individuals have more complex problems and engage in more CA and PSA than non-depressed and (2) the effects of CA and PSA on decreases in problem complexity, depressive symptoms, and remission from the depression. Samples of 85 patients were treated for depression with antidepressants and psychotherapy, and 49 healthy subjects were assessed three times over a 4-month period (at Weeks 1, 5, and 16). At each assessment, they completed measures of depression, analytical rumination, and problem complexity. Depressed individuals reported having more complex problems and engaging in more CA than non-depressed participants. The two groups engaged in a similar degree of PSA. Findings from a multiple regression suggested that more PSA at Week 1 was related to a decrease in depressive symptoms at Week 5, even after controlling for baseline depression, problem number, and complexity. PSA at Week 1 did not predict the remission after hospitalization or at follow-up; however, having less complex problems at the baseline made it more likely that a patient would later remit. Engaging in more CA or PSA at Week 1 did not affect perceived problem complexity at Week 5 or at follow-up. However, these findings were not statistically significant when influential observations (or outliers) were included in the analysis. Our findings suggest that PSA may contribute to a decrease in symptoms of depression over time. However, alleviations in problem complexity and remission might only be achieved if problems are initially less complex. Future directions involve exploring how PSA might contribute to decreases in depressive symptoms and other mechanisms underlying remission from depression.
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