Deutsches Institut für Internationale Pädagogische Forschung (DIPF)
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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.