Deutsches Institut für Internationale Pädagogische Forschung (DIPF)
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Older adults show relatively minor age-related decline in memory for single items, while their memory for associations is markedly reduced. Inter-individual differences in memory function in older adults are substantial but the neurobiological underpinnings of such differences are not well understood. In particular, the relative importance of inter-individual differences in the medio-temporal lobe (MTL) and the lateral prefrontal cortex (PFC) for associative and item recognition in older adults is still ambiguous. We therefore aimed to first establish the distinction between inter-individual differences in associative memory (recollection-based) performance and item memory (familiarity-based) performance in older adults and subsequently link these two constructs to differences in cortical thickness in the MTL and lateral PFC regions, in a latent structural equation modelling framework. To this end, a sample of 160 older adults (65–75 years old) performed three intentional item-associative memory tasks, of which a subsample (n = 72) additionally had cortical thickness measures in MTL and PFC regions of interest available. The results provided support for a distinction between familiarity-based item memory and recollection-based associative memory performance in older adults. Cortical thickness in the ventro-medial prefrontal cortex was positively correlated with associative recognition performance, above and beyond any relationship between item recognition performance and cortical thickness in the same region and between associative recognition performance and brain structure in the MTL (parahippocampus). The findings highlight the relative importance of the ventromedial prefrontal cortex in allowing for intentional recollection-based associative memory functioning in older adults.
This study examined age‐related differences in the effectiveness of two generative learning strategies (GLSs). Twenty‐five children aged 9–11 and 25 university students aged 17–29 performed a facts learning task in which they had to generate either a prediction or an example before seeing the correct result. We found a significant Age × Learning Strategy interaction, with children remembering more facts after generating predictions rather than examples, whereas both strategies were similarly effective in adults. Pupillary data indicated that predictions stimulated surprise, whereas the effectiveness of example‐based learning correlated with children’s analogical reasoning abilities. These findings suggest that there are different cognitive prerequisites for different GLSs, which results in varying degrees of strategy effectiveness by age.
This study investigated whether prompting children to generate predictions about an outcome facilitates activation of prior knowledge and improves belief revision. 51 children aged 9–12 were tested on two experimental tasks in which generating a prediction was compared to closely matched control conditions, as well as on a test of executive functions (EF). In Experiment 1, we showed that children exhibited a pupillary surprise response to events that they had predicted incorrectly, hypothesized to reflect the transient release of noradrenaline in response to cognitive conflict. However, children's surprise response was not associated with better belief revision, in contrast to a previous study involving adults. Experiment 2 revealed that, while generating predictions helped children activate their prior knowledge, only those with better inhibitory control skills learned from incorrectly predicted outcomes. Together, these results suggest that good inhibitory control skills are needed for learning through cognitive conflict. Thus, generating predictions benefits learning – but only among children with sufficient EF capacities to harness surprise for revising their beliefs.
We tested 6–7-year-olds, 18–22-year-olds, and 67–74-year-olds on an associative memory task that consisted of knowledge-congruent and knowledge-incongruent object–scene pairs that were highly familiar to all age groups. We compared the three age groups on their memory congruency effect (i.e., better memory for knowledge-congruent associations) and on a schema bias score, which measures the participants’ tendency to commit knowledge-congruent memory errors. We found that prior knowledge similarly benefited memory for items encoded in a congruent context in all age groups. However, for associative memory, older adults and, to a lesser extent, children overrelied on their prior knowledge, as indicated by both an enhanced congruency effect and schema bias. Functional Magnetic Resonance Imaging (fMRI) performed during memory encoding revealed an age-independent memory x congruency interaction in the ventromedial prefrontal cortex (vmPFC). Furthermore, the magnitude of vmPFC recruitment correlated positively with the schema bias. These findings suggest that older adults are most prone to rely on their prior knowledge for episodic memory decisions, but that children can also rely heavily on prior knowledge that they are well acquainted with. Furthermore, the fMRI results suggest that the vmPFC plays a key role in the assimilation of new information into existing knowledge structures across the entire lifespan. vmPFC recruitment leads to better memory for knowledge-congruent information but also to a heightened susceptibility to commit knowledge-congruent memory errors, in particular in children and older adults.
Learning to solve graph tasks is one of the key prerequisites of acquiring domain-specific knowledge in most study domains. Analyses of graph understanding often use eye-tracking and focus on analyzing how much time students spend gazing at particular areas of a graph—Areas of Interest (AOIs). To gain a deeper insight into students’ task-solving process, we argue that the gaze shifts between students’ fixations on different AOIs (so-termed transitions) also need to be included in holistic analyses of graph understanding that consider the importance of transitions for the task-solving process. Thus, we introduced Epistemic Network Analysis (ENA) as a novel approach to analyze eye-tracking data of 23 university students who solved eight multiple-choice graph tasks in physics and economics. ENA is a method for quantifying, visualizing, and interpreting network data allowing a weighted analysis of the gaze patterns of both correct and incorrect graph task solvers considering the interrelations between fixations and transitions. After an analysis of the differences in the number of fixations and the number of single transitions between correct and incorrect solvers, we conducted an ENA for each task. We demonstrate that an isolated analysis of fixations and transitions provides only a limited insight into graph solving behavior. In contrast, ENA identifies differences between the gaze patterns of students who solved the graph tasks correctly and incorrectly across the multiple graph tasks. For instance, incorrect solvers shifted their gaze from the graph to the x-axis and from the question to the graph comparatively more often than correct solvers. The results indicate that incorrect solvers often have problems transferring textual information into graphical information and rely more on partly irrelevant parts of a graph. Finally, we discuss how the findings can be used to design experimental studies and for innovative instructional procedures in higher education
Sleep and Attention-Deficit/Hyperactivity Disorder (ADHD) have repeatedly been found to be associated with each other. However, the ecological validity of daily life studies to examine the effect of sleep on ADHD symptoms is rarely made use of. In an ambulatory assessment study with measurement burst design, consisting of three bursts (each 6 months apart) of 18 days each, 70 German schoolchildren aged 10–12 years reported on their sleep quality each morning and on their subjective ADHD symptom levels as well as their sleepiness three times a day. It was hypothesized that nightly sleep quality is negatively associated with ADHD symptoms on the inter- as well as the intraindividual level. Thus, we expected children who sleep better to report higher attention and self-regulation. Additionally, sleepiness during the day was hypothesized to be positively associated with ADHD symptoms on both levels, meaning that when children are sleepier, they experience more ADHD symptoms. No association of sleep quality and ADHD symptoms between or within participants was found in multilevel analyses; also, no connection was found between ADHD symptoms and daytime sleepiness on the interindividual level. Unexpectedly, a negative association was found on the intraindividual level for ADHD symptoms and daytime sleepiness, indicating that in moments when children are sleepier during the day, they experience less ADHD symptoms. Explorative analyses showed differential links of nightly sleep quality and daytime sleepiness, with the core symptoms of inattention and hyperactivity/impulsivity, respectively. Therefore, future analyses should take the factor structure of ADHD symptoms into account.
The effects of aging on response time were examined in a paper-based lexical-decision experiment with younger (age 18–36) and older (age 64–75) adults, applying Ratcliff’s diffusion model. Using digital pens allowed the paper-based assessment of response times for single items. Age differences previously reported by Ratcliff and colleagues in computer-based experiments were partly replicated: older adults responded more conservatively than younger adults and showed a slowing of their nondecision components of RT by 53 ms. The rates of evidence accumulation (drift rate) showed no age-related differences. Participants with a higher score in a vocabulary test also had higher drift rates. The experiment demonstrates the possibility to use formal processing models with paper-based tests.
The purpose of the present study was to examine the effects of cooperative training strategies to enhance students' socioscientific decision making as well as their metacognitive skills in the science classroom. Socioscientific decision making refers to both “describing socioscientific issues” as well as “developing and evaluating solutions” to socioscientific issues. We investigated two cooperative training strategies which differed with respect to embedded metacognitive instructions that were developed on the basis of the IMPROVE method. Participants were 360 senior high school students who studied either in a cooperative learning setting (COOP), a cooperative learning setting with embedded metacognitive questions (COOP+META), or a nontreatment control group. Results indicate that students in the two training conditions outperformed students in the control group on both processes of socioscientific decision making. However, students in the COOP+META condition did not outperform students in the COOP condition. With respect to students' learning outcomes on the regulation facet of metacognition, results indicate that all conditions improved over time. Students in the COOP+META condition exhibited highest mean scores at posttest measures, but again, results were not significant. Implications for integrating metacognitive instructions into science classrooms are discussed.
Complex problem solving (CPS) is a highly transversal competence needed in educational and vocational settings as well as everyday life. The assessment of CPS is often computer-based, and therefore provides data regarding not only the outcome but also the process of CPS. However, research addressing this issue is scarce. In this article we investigated planning activities in the process of complex problem solving. We operationalized planning through three behavioral measures indicating the duration of the longest planning interval, the delay of the longest planning interval and the variance of intervals between each two successive interactions. We found a significant negative average effect for our delay indicator, indicating that early planning in CPS is more beneficial. However, we also found effects depending on task and interaction effects for all three indicators, suggesting that the effects of different planning behaviors on CPS are highly intertwined.
In this explorative study, we investigate how sequences of behaviour are related to success or failure in complex problem‐solving (CPS). To this end, we analysed log data from two different tasks of the problem‐solving assessment of the Programme for International Student Assessment 2012 study (n = 30,098 students). We first coded every interaction of students as (initial or repeated) exploration, (initial or repeated) goal‐directed behaviour, or resetting the task. We then split the data according to task successes and failures. We used full‐path sequence analysis to identify groups of students with similar behavioural patterns in the respective tasks. Double‐checking and minimalistic behaviour was associated with success in CPS, while guessing and exploring task‐irrelevant content was associated with failure. Our findings held for both tasks investigated, from two different CPS measurement frameworks. We thus gained detailed insight into the behavioural processes that are related to success and failure in CPS.