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.
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.
Early experiences of childhood sexual or physical abuse are often associated with functional impairments, reduced well-being and interpersonal problems in adulthood. Prior studies have addressed whether the traumatic experience itself or adult psychopathology is linked to these limitations. To approach this question, individuals with posttraumatic stress disorder (PTSD) and healthy individuals with and without a history of child abuse were investigated. We used global positioning system (GPS) tracking to study temporal and spatial limitations in the participants’ real-life activity space over the course of one week. The sample consisted of 228 female participants: 150 women with PTSD and emotional instability with a history of child abuse, 35 mentally healthy women with a history of child abuse (healthy trauma controls, HTC) and 43 mentally healthy women without any traumatic experiences in their past (healthy controls, HC). Both traumatized groups—i.e. the PTSD and the HTC group—had smaller movement radii than the HC group on the weekends, but neither spent significantly less time away from home than HC. Some differences between PTSD and HC in movement radius seem to be related to correlates of PTSD psychopathology, like depression and physical health. Yet group differences between HTC and HC in movement radius remained even when contextual and individual health variables were included in the model, indicating specific effects of traumatic experiences on activity space. Experiences of child abuse could limit activity space later in life, regardless of whether PTSD develops.
Cognitive modeling studies in adults have established that visual working memory (WM) capacity depends on the representational precision, as well as its variability from moment to moment. By contrast, visuospatial WM performance in children has been typically indexed by response accuracy—a binary measure that provides less information about precision with which items are stored. Here, we aimed at identifying whether and how children’s WM performance depends on the spatial precision and its variability over time in real-world contexts. Using smartphones, 110 Grade 3 and Grade 4 students performed a spatial WM updating task three times a day in school and at home for four weeks. Measures of spatial precision (i.e., Euclidean distance between presented and reported location) were used for hierarchical modeling to estimate variability of spatial precision across different time scales. Results demonstrated considerable within-person variability in spatial precision across items within trials, from trial to trial and from occasion to occasion within days and from day to day. In particular, item-to-item variability was systematically increased with memory load and lowered with higher grade. Further, children with higher precision variability across items scored lower in measures of fluid intelligence. These findings emphasize the important role of transient changes in spatial precision for the development of WM.
Multi-scale entropy (MSE) has been recently established as a promising tool for the analysis of the moment-to-moment variability of neural signals. Appealingly, MSE provides a measure of the predictability of neural operations across the multiple time scales on which the brain operates. An important limitation in the application of the MSE to some classes of neural signals is MSE's apparent reliance on long time series. However, this sparse-data limitation in MSE computation could potentially be overcome via MSE estimation across shorter time series that are not necessarily acquired continuously (e.g., in fMRI block-designs). In the present study, using simulated, EEG, and fMRI data, we examined the dependence of the accuracy and precision of MSE estimates on the number of data points per segment and the total number of data segments. As hypothesized, MSE estimation across discontinuous segments was comparably accurate and precise, despite segment length. A key advance of our approach is that it allows the calculation of MSE scales not previously accessible from the native segment lengths. Consequently, our results may permit a far broader range of applications of MSE when gauging moment-to-moment dynamics in sparse and/or discontinuous neurophysiological data typical of many modern cognitive neuroscience study designs.
Imageability and emotionality ratings for 2592 German nouns (3–10 letters, one to three phonological syllables) were obtained from younger adults (21–31 years) and older adults (70–86 years). Valid ratings were obtained on average from 20 younger and 23 older adults per word for imageability, and from 18 younger and 19 older adults per word for emotionality. The internal consistency (Cronbach’s α) and retest rank-order stability of the ratings were high for both age groups (α and r ≥ .97). Also, the validity of our ratings was found to be high, as compared to previously published ratings (r ≥ .86). The ratings showed substantial rank-order stability across younger and older adults (imageability, r = .94; emotionality, r = .85). At the same time, systematic differences between age groups were found in the mean levels of ratings (imageability, d = 0.38; emotionality, d = 0.20) and in the extent to which the rating scales were used (imageability, SD = 24 vs. 19, scale of 0 to 100; emotionality, SD = 26 vs. 31, scale of −100 to 100). At the descriptive level, our data hint at systematically different evaluations of semantic categories regarding imageability and emotionality across younger and older adults. Given that imageability and emotionality have been reported, for instance, as important determinants for the recognition and recall of words, our findings highlight the importance of considering age-specific information in age-comparative cognitive (neuroscience) experimental studies using word materials. The age-specific imageability and emotionality ratings for the 2592 German nouns can be found in the electronic supplementary material...
Objective: Although meaning making and specifically autobiographical reasoning are expected to relate to well‐being, findings tend to be mixed. Attempts at meaning making do not always lead to meaning made. We aimed to disentangle these complex relationships and also explore the role of level of education.
Method: Ninety participants (mean age 36.73 years, SD = 7.27; 74.4% women, 25.6% men) who had experienced the loss of a parent through death, going missing, or Alzheimer's disease narrated this loss, a sad, a turning point, and a self‐defining memory, and completed questionnaires assessing depression, trauma symptoms, and protracted grief. Three aspects of autobiographical reasoning (quantity, valence, and change‐relatedness of self‐event connections) were related to meaning made (sophistication of meaning making) and symptom level.
Results: Years of education correlated both with positive implications of autobiographical reasoning and with meaning made. The quantity, positivity, and change‐relatedness of attempts at meaning making (self‐event connections) predicted accomplished meaning made, and positivity alone predicted less prolonged grief.
Conclusions: Adapting the life story after a loss such that change of the self is acknowledged and positive change can be constructed helps finding meaning and lowering protracted grief. These changes in narrative identity are supported by more years of education.
Based on neurofeedback (NF) training as a neurocognitive treatment in attention-deficit/hyperactivity disorder (ADHD), we designed a randomized, controlled functional near-infrared spectroscopy (fNIRS) NF intervention embedded in an immersive virtual reality classroom in which participants learned to control overhead lighting with their dorsolateral prefrontal brain activation. We tested the efficacy of the intervention on healthy adults displaying high impulsivity as a sub-clinical population sharing common features with ADHD. Twenty participants, 10 in an experimental and 10 in a shoulder muscle-based electromyography control group, underwent eight training sessions across 2 weeks. Training was bookended by a pre- and post-test including go/no-go, n-back, and stop-signal tasks (SST). Results indicated a significant reduction in commission errors on the no-go task with a simultaneous increase in prefrontal oxygenated hemoglobin concentration for the experimental group, but not for the control group. Furthermore, the ability of the subjects to gain control over the feedback parameter correlated strongly with the reduction in commission errors for the experimental, but not for the control group, indicating the potential importance of learning feedback control in moderating behavioral outcomes. In addition, participants of the fNIRS group showed a reduction in reaction time variability on the SST. Results indicate a clear effect of our NF intervention in reducing impulsive behavior possibly via a strengthening of frontal lobe functioning. Virtual reality additions to conventional NF may be one way to improve the ecological validity and symptom-relevance of the training situation, hence positively affecting transfer of acquired skills to real life.
Highlights
• Transparency of design, reference frames and support for action were found to support students' sense-making of LA dashboards.
• The higher the overall SRL score, the more relevant the three factors were perceived by learners.
• Learner goals affect how relevant students find reference frames.
• The SRL effect on the perceived relevance of transparency depends on learner goals.
Abstract
Unequal stakeholder engagement is a common pitfall of adoption approaches of learning analytics in higher education leading to lower buy-in and flawed tools that fail to meet the needs of their target groups. With each design decision, we make assumptions on how learners will make sense of the visualisations, but we know very little about how students make sense of dashboard and which aspects influence their sense-making. We investigated how learner goals and self-regulated learning (SRL) skills influence dashboard sense-making following a mixed-methods research methodology: a qualitative pre-study followed-up with an extensive quantitative study with 247 university students. We uncovered three latent variables for sense-making: transparency of design, reference frames and support for action. SRL skills are predictors for how relevant students find these constructs. Learner goals have a significant effect only on the perceived relevance of reference frames. Knowing which factors influence students' sense-making will lead to more inclusive and flexible designs that will cater to the needs of both novice and expert learners.
In this paper, we developed a method to extract item-level response times from log data that are available in computer-based assessments (CBA) and paper-based assessments (PBA) with digital pens. Based on response times that were extracted using only time differences between responses, we used the bivariate generalized linear IRT model framework (B-GLIRT, [1]) to investigate response times as indicators for response processes. A parameterization that includes an interaction between the latent speed factor and the latent ability factor in the cross-relation function was found to fit the data best in CBA and PBA. Data were collected with a within-subject design in a national add-on study to PISA 2012 administering two clusters of PISA 2009 reading units. After investigating the invariance of the measurement models for ability and speed between boys and girls, we found the expected gender effect in reading ability to coincide with a gender effect in speed in CBA. Taking this result as indication for the validity of the time measures extracted from time differences between responses, we analyzed the PBA data and found the same gender effects for ability and speed. Analyzing PBA and CBA data together we identified the ability mode effect as the latent difference between reading measured in CBA and PBA. Similar to the gender effect the mode effect in ability was observed together with a difference in the latent speed between modes. However, while the relationship between speed and ability is identical for boys and girls we found hints for mode differences in the estimated parameters of the cross-relation function used in the B-GLIRT model.
As a relevant cognitive-motivational aspect of ICT literacy, a new construct ICT Engagement is theoretically based on self-determination theory and involves the factors ICT interest, Perceived ICT competence, Perceived autonomy related to ICT use, and ICT as a topic in social interaction. In this manuscript, we present different sources of validity supporting the construct interpretation of test scores in the ICT Engagement scale, which was used in PISA 2015. Specifically, we investigated the internal structure by dimensional analyses and investigated the relation of ICT Engagement aspects to other variables. The analyses are based on public data from PISA 2015 main study from Switzerland (n = 5860) and Germany (n = 6504). First, we could confirm the four-dimensional structure of ICT Engagement for the Swiss sample using a structural equation modelling approach. Second, ICT Engagement scales explained the highest amount of variance in ICT Use for Entertainment, followed by Practical use. Third, we found significantly lower values for girls in all ICT Engagement scales except ICT Interest. Fourth, we found a small negative correlation between the scores in the subscale “ICT as a topic in social interaction” and reading performance in PISA 2015. We could replicate most results for the German sample. Overall, the obtained results support the construct interpretation of the four ICT Engagement subscales.
Background: Recent studies have suggested substantial fluctuations of cognitive performance in adults both across and within days, but very little is known about such fluctuations in children. Children's sleep behavior might have an important influence on their daily cognitive resources, but so far this has not been investigated in terms of naturally occurring within-person variations in children's everyday lives.
Methods: In an ambulatory assessment study, 110 elementary school children (8–11 years old) completed sleep items and working memory tasks on smartphones several times per day in school and at home for 4 weeks. Parents provided general information about the children and their sleep habits.
Results: We identified substantial fluctuations in the children's daily cognitive performance, self-reported nightly sleep quality, time in bed, and daytime tiredness. All three facets were predictive of performance fluctuations in children's school and daily life. Sleep quality and time in bed were predictive of performance in the morning, and afternoon performance was related to current tiredness. The children with a lower average performance level showed a higher within-person coupling between morning performance and sleep quality.
Conclusions: Our findings contribute important insights regarding a potential source of performance fluctuations in children. The effect of varying cognitive resources should be investigated further because it might impact children's daily social, emotional, and learning-related functioning. Theories about children's cognitive and educational development should consider fluctuations on micro-longitudinal scales (e.g., day-to-day) to identify possible mechanisms behind long-term changes.