Individual Subjects Research Articles

Systematic review of drug-drug interactions of delta-9-tetrahydrocannabinol, cannabidiol, and Cannabis.

The recent exponential increase in legalized medical and recreational cannabis, development of medical cannabis programs, and production of unregulated over-the-counter products (e.g., cannabidiol (CBD) oil, and delta-8-tetrahydrocannabinol (delta-8-THC)), has the potential to create unintended health consequences. The major cannabinoids (delta-9-tetrahydrocannabinol and cannabidiol) are metabolized by the same cytochrome P450 (CYP) enzymes that metabolize most prescription medications and xenobiotics (CYP3A4, CYP2C9, CYP2C19). As a result, we predict that there will be instances of drug-drug interactions and the potential for adverse outcomes, especially for prescription medications with a narrow therapeutic index. We conducted a systematic review of all years to 2023 to identify real world reports of documented cannabinoid interactions with prescription medications. We limited our search to a set list of medications with predicted narrow therapeutic indices that may produce unintended adverse drug reactions (ADRs). Our team screened 4,600 reports and selected 151 full-text articles to assess for inclusion and exclusion criteria. Our investigation revealed 31 reports for which cannabinoids altered pharmacokinetics and/or produced adverse events. These reports involved 16 different Narrow Therapeutic Index (NTI) medications, under six drug classes, 889 individual subjects and 603 cannabis/cannabinoid users. Interactions between cannabis/cannabinoids and warfarin, valproate, tacrolimus, and sirolimus were the most widely reported and may pose the greatest risk to patients. Common ADRs included bleeding risk, altered mental status, difficulty inducing anesthesia, and gastrointestinal distress. Additionally, we identified 18 instances (58%) in which clinicians uncovered an unexpected serum level of the prescribed drug. The quality of pharmacokinetic evidence for each report was assessed using an internally developed ten-point scale. Drug-drug interactions with cannabinoids are likely amongst prescription medications that use common CYP450 systems. Our findings highlight the need for healthcare providers and patients/care-givers to openly communicate about cannabis/cannabinoid use to prevent unintended adverse events. To that end, we have developed a free online tool (www.CANN-DIR.psu.edu) to help identify potential cannabinoid drug-drug interactions with prescription medications.

Multiple Image Distortion DNN Modeling Individual Subject Quality Assessment

A recent research direction is focused on training Deep Neural Networks (DNNs) to replicate individual subject assessments of media quality. These DNNs are referred to as Artificial Intelligence-based Observers (AIOs). An AIO is designed to simulate, in real-time, the quality ratings of a specific individual, enabling an automatic quality assessment that accounts for subjects characteristics and preferences. Training AIOs is a promising but challenging research area due to the greater noise in individual raw opinion scores compared to the Mean Opinion Score (MOS). Effective learning from noisy labels necessitates the training of complex models on large-scale datasets. Unfortunately, this is challenging for AIOs as the media quality assessment community lacks extensive datasets that include individual opinion scores. To address the complexity of the task, we first created a dataset comprising two million samples, with synthetic labels derived from human annotation. We then trained a customized network for image quality assessment, named Multi-Distortion ResNet50 (MDResNet50), on this dataset. The weights of the MDResNet50 were subsequently utilized to initialize the learning process of each AIO, thereby avoiding the need to train a complex model from scratch on a small-scale dataset with raw individual opinion scores. Computational experiments show that our approach significantly advances the state-of-the-art in the AIO research. In particular: i) we demonstrate through a simulation the ability of AIOs to mimic two well-known behavioral characteristics of a subject, i.e.,bias and inconsistency, when scoring the media quality; ii) we train and release DNN-based AIOs that, compared to the state-of-the-art, exhibit a higher performance with a statistical significance in assessing multiple image distortions; iii) we train AIOs that more accurately mimic the sensitivity of real subjects to noise and color saturation, and also better predict the opinion score distribution compared to the state-of-the-art AIOs.

The molecular landscape of sepsis severity in infants: enhanced coagulation, innate immunity, and T cell repression.

Sepsis remains a major cause of mortality and morbidity in infants. In recent years, several gene marker strategies for the early identification of sepsis have been proposed but only a few have been independently validated for adult cohorts and applicability to infant sepsis remains unclear. Biomarkers to assess disease severity and risks of shock also represent an important unmet need. To elucidate characteristics driving sepsis in infants, we assembled a multi-transcriptomic dataset from public microarray datasets originating from five independent studies pertaining to bacterial sepsis in infant < 6-months of age (total n=335). We utilized a COmbat co-normalization strategy to enable comparative evaluation across multiple studies while preserving the relationship between cases and controls. We found good concordance with only two out of seven of the published adult sepsis gene signatures (accuracy > 80%), highlighting the narrow utility of adult-derived signatures for infant diagnosis. Pseudotime analysis of individual subjects' gene expression profiles showed a continuum of molecular changes forming tight clusters concurrent with disease progression between healthy controls and septic shock cases. In depth gene expression analyses between bacteremia, septic shock, and healthy controls characterized lymphocyte activity, hemostatic processes, and heightened innate immunity during the molecular transition toward a state of shock. Our analysis revealed the presence of multiple significant transcriptomic perturbations that occur during the progression to septic shock in infants that are characterized by late-stage induction of clotting factors, in parallel with a heightened innate immune response and a suppression of adaptive cell functionality.

Spatio-temporal dynamics of the human small intestinal microbiome and its response to a synbiotic

ABSTRACT Although fecal microbiota composition is considered to preserve relevant and representative information for distal colonic content, it is evident that it does not represent microbial communities inhabiting the small intestine. Nevertheless, studies investigating the human small intestinal microbiome and its response to dietary intervention are still scarce. The current study investigated the spatio-temporal dynamics of the small intestinal microbiome within a day and over 20 days, as well as its responses to a 14-day synbiotic or placebo control supplementation in 20 healthy subjects. Microbial composition and metabolome of luminal content of duodenum, jejunum, proximal ileum and feces differed significantly from each other. Additionally, differences in microbiota composition along the small intestine were most pronounced in the morning after overnight fasting, whereas differences in composition were not always measurable around noon or in the afternoon. Although overall small intestinal microbiota composition did not change significantly within 1 day and during 20 days, remarkable, individual-specific temporal dynamics were observed in individual subjects. In response to the synbiotic supplementation, only the microbial diversity in jejunum changed significantly. Increased metabolic activity of probiotic strains during intestinal passage, as assessed by metatranscriptome analysis, was not observed. Nevertheless, synbiotic supplementation led to a short-term spike in the relative abundance of genera included in the product in the small intestine approximately 2 hours post-ingestion. Collectively, small intestinal microbiota are highly dynamic. Ingested probiotic bacteria could lead to a transient spike in the relative abundance of corresponding genera and ASVs, suggesting their passage through the entire gastrointestinal tract. This study was registered to http://www.clinicaltrials.gov, NCT02018900.

Pengembangan E-Booklet Berbasis Aplikasi Android Pada Sub Konsep Sistem Peredaran Darah Manusia Kelas XI SMA

Electronic booklets are learning resources that are in accordance with online learning conditions, the 2013 curriculum and IT advances in education. The research model used is 4D namely: 1) Define, 2) Design and 3) Development which then in the Development stage uses the Tessmer Formative Evaluation design namely 1) Expert assessment and 2) individual test 3) small group test. The subjects of the validity test were 2 Biology Education lecturers and 1 Biology teacher at SMA Negeri 4 Banjarmasin. The individual test subjects were 3 class XI MIPA 3 students at SMA Negeri 4 Banjarmasin and the small group test subjects were 4 students in the same class. The results of the study show 1) the validity of the Android application-based E-Booklet based on 5 aspects has a valid category; 2) the practicality of the contents of the Android application-based E-Booklet has attractiveness based on the responses of students in the at least good category, the practicality of the hope that the E-Booklet is easy to use based on the responses of students in the least good category; and 3) the effectiveness of expectations based on critical thinking assessments obtains a very good category in interpretation, analysis, evaluation, explanation, and self-regulation skills, and has a good category in the aspect of inference

Data-Fusion-Based Quality Enhancement for HR Measurements Collected by Wearable Sensors.

The advancements of Internet of Things (IoT) technologies have enabled the implementation of smart and wearable sensors, which can be employed to provide older adults with affordable and accessible continuous biophysiological status monitoring. The quality of such monitoring data, however, is unsatisfactory due to excessive noise induced by various disturbances, such as motion artifacts. Existing methods take advantage of summary statistics, such as mean or median values, for denoising, without taking into account the biophysiological patterns embedded in data. In this research, a functional data analysis modeling method was proposed to enhance the data quality by learning individual subjects' diurnal heart rate (HR) patterns from historical data, which were further improved by fusing newly collected data. This proposed data-fusion approach was developed based on a Bayesian inference framework. Its effectiveness was demonstrated in an HR analysis from a prospective study involving older adults residing in assisted living or home settings. The results indicate that it is imperative to conduct personalized healthcare by estimating individualized HR patterns. Furthermore, the proposed calibration method provides a more accurate (smaller mean errors) and more precise (smaller error standard deviations) HR estimation than raw HR and conventional methods, such as the mean.

Data leakage in deep learning studies of translational EEG.

A growing number of studies apply deep neural networks (DNNs) to recordings of human electroencephalography (EEG) to identify a range of disorders. In many studies, EEG recordings are split into segments, and each segment is randomly assigned to the training or test set. As a consequence, data from individual subjects appears in both the training and the test set. Could high test-set accuracy reflect data leakage from subject-specific patterns in the data, rather than patterns that identify a disease? We address this question by testing the performance of DNN classifiers using segment-based holdout (in which segments from one subject can appear in both the training and test set), and comparing this to their performance using subject-based holdout (where all segments from one subject appear exclusively in either the training set or the test set). In two datasets (one classifying Alzheimer's disease, and the other classifying epileptic seizures), we find that performance on previously-unseen subjects is strongly overestimated when models are trained using segment-based holdout. Finally, we survey the literature and find that the majority of translational DNN-EEG studies use segment-based holdout. Most published DNN-EEG studies may dramatically overestimate their classification performance on new subjects.

Drug use survey to identify significant drug-drug interactions and assess clinical importance in the outpatient setting of a tertiary care hospital.

Drug-drug interactions (DDIs) are a common problem in pharmacotherapy, particularly in situations where multiple disorders must be treated at the same time. We conducted a drug use survey in the general medicine outpatient department of a tertiary care hospital with the objective of assessing the potential for DDI in individual prescriptions for adult patients. Drugs prescribed in the current physician-patient encounter were considered in conjunction with medicines already being received by the patient as well as those discontinued in the past 1 month. Free online DDI checkers (available at https://www.drugs.com/drug_interactions.html and https://reference.medscape.com/) were used to identify potential DDI and categorize them into mild, moderate, and severe categories. We did not consider food, alcohol, or smoking-related interactions. A total of 153 prescriptions, having two or more drugs, were collected, and they accounted for 1052 prescribed drugs. Among them, 613 (58.27%) were prescribed in index visits, and the rest 438 (41.63%) were preexisting medication. The number of drugs prescribed in index visits ranged from 1 to 9 (mean ± standard deviation [SD] 4.0 ± 1.86; median 4). Potential DDIs were identified in 103 (67.32%) instances. The total number of interactions identified was 412. Of these, 19.66% had minor, 77.67% moderate, and 7.19% major clinical implications. Potential DDI count in each prescription was found from 0 to 13 in number (mean ± SD 2.7 ± 3.12; median 2.0). This number correlated strongly with the number of drugs being received by individual subjects (Rho 0.744; P < 0.001). Potential DDIs are a reality in day to day prescribing practice. Substantial proportion of these DDIs may have significant clinical implications. Prescribers need to be sensitized to this issue. Combining human expertise with technological solutions such as automated drug interaction alerts can help rectify the situation. Similar surveys are needed on a periodic basis to improve medication safety for patients.

Interactions-based classification of a single microbial sample

To address the limitation of overlooking crucial ecological interactions due to relying on single time point samples, we developed a computational approach that analyzes individual samples based on the interspecific microbial relationships. We verify, using both numerical simulations as well as real and shuffled microbial profiles from the human oral cavity, that the method can classify single samples based on their interspecific interactions. By analyzing the gut microbiome of people with autistic spectrum disorder, we found that our interaction-based method can improve the classification of individual subjects based on a single microbial sample. These results demonstrate that the underlying ecological interactions can be practically utilized to facilitate microbiome-based diagnosis and precision medicine.

Measurement of somatosensory evoked magnetic fields using an adjustable magnetoresistive sensor array

An adjustable helmet-style magnetoresistive (MR) sensor array with room-temperature magnetic flux sensors was developed to demonstrate the simultaneous multipoint measurement of the somatosensory evoked magnetic field (SEF). Utilizing the extended sensor length, we designed the array to permit individual radial adjustment of each sensor, thereby achieving a precise fit to the varied head geometries of different subjects. Furthermore, the geometry of the sensor array precisely adjusted for the individual subject was quickly obtained by calibration. The SEF was measured in three healthy subjects using an array of 30-channel MR sensors placed on the left hemisphere of the head with median nerve stimulation in the right wrist and averaged over 8000 measurements. An M20 component considered to originate from the primary somatosensory cortex was observed at an approximate latency of 20 ms of the magnetic field waveform in all cases (maximum amplitude of 725 ± 257 fT, peak latency of 20.5 ± 0.45 ms). The phase inversion observed around C3 in the international 10–20 system corresponded to the palmar area of the primary somatosensory cortex on the contour map of the magnetic field at the M20 peak. The MR sensor, an affordable and easy-to-use magnetic sensor that does not require a zero-field environment nor a cryogenic apparatus, was successfully used for simultaneous multipoint SEF measurements in humans and provides a promising system for realizing magnetoencephalography application devices.

A new philosophy for international legal skepticism?

Abstract Ronald Dworkin maintains that a system of coercive government is a genuinely legal one if and only if it exhibits fidelity to a conception of the rule of law as valuable for the constitutive contribution it makes to the treatment of all its individual human subjects with equal concern and respect. This requires a particular type of institutional structure, namely one that satisfies the criteria that constitute government according to the rule of law, and a particular political culture or ethos on the part of both rulers and ruled that Dworkin labels law as integrity. The existing practice of global coercive government may well satisfy neither of these conditions. If so, then given Dworkin's account of law, international law is not really law. Importantly, this is a practical claim, not a descriptive/explanatory one. Specifically, it entails that international officials are sometimes morally permitted to tell noble lies regarding what the ‘law’ is, to refuse to pronounce on questions of ‘law’, and to refrain from applying and enforcing actors' ‘legal’ rights and duties.

Toward an African Critical Orientation

ABSTRACT This essay proposes an African orientation to critical work. We begin by locating the need for postcolonial indigenous African bases for critical interventions in the idea of epistemic freedom articulated by African decolonial thinkers along with the postcolonial critique of Frankfurt School and Chicago circle critical theory. Next, we develop a basis for critical interventions in Bantu cosmology by drawing on Omedi Ochieng’s groundwork thesis and applied sociolinguistics. That basis, we argue, prioritizes relatedness and community wellbeing, and is therefore broader and distinct from the narrow focus on power and domination as they relate to individual subject envisioned in liberalism. We illustrate the heuristic potential of the African critical orientation for critical intercultural and critical rhetorical work by discussing the African Medical and Research Foundation’s (AMREF) Mukogodo community organizational development initiative and the #Rhodesmustfall protests of 2015–2016.

Why the racing industry and equestrian disciplines need to implement population pharmacokinetics: To learn, explain, summarize, harmonize, and individualize.

Population pharmacokinetics (POP PK) is a powerful pharmacokinetic tool, which measures quantitatively, and explains the variability in drug exposure and drug effect between individuals. POP PK uses an observational (nonexperimental) approach; it is conducted in the target population living in its normal environment (e.g., farm and race-track). The strength of the POP PK approach lies in its greater relevance for the population studied in its different natural environments than experimental studies carried out in more or less biased laboratory conditions. In clinical settings, it is commonly necessary to restrict the number of samples per subject collected for analysis and the derived data cannot be analyzed using traditional individual data analytical methods; rather data are merged and analyzed with an appropriate statistical tool: the nonlinear mixed effect model (NLMEM). POP PK modeling is frequently used with the objective of adjusting drug dosage, and hence drug exposure, not only for the whole population but also for subgroups of animals (e.g., for a given breed, sex, and age). It can also have application at the individual subject level, in the context of precision medicine. For horses, the use of the POP PK/PD model will allow prescribers to estimate an individual Withdrawal Time for a given horse whose treatment they are supervising. Another potential field of application will be meta-analysis of existing data to generate new knowledge on a drug or to collate and synthesize, in an objective and transparent manner, existing data; this will facilitate harmonization of screening limits at an international level.

Clustering index analysis on EMG-Torque relation-based representation of complex neuromuscular changes after spinal cord injury

Spinal cord injury (SCI) resulting in complex neuromuscular pathology is not sufficiently well understood. To better quantify neuromuscular changes after SCI, this study uses a clustering index (CI) method for surface electromyography (sEMG) clustering representation to investigate the relation between sEMG and torque in SCI survivors. The sEMG signals were recorded from 13 subjects with SCI and 13 gender-age matched able-bodied subjects during isometric contraction of the biceps brachii muscle at different torque levels using a linear electrode array. Two torque representations, maximum voluntary contraction (MVC%) and absolute torque, were used. CI values were calculated for sEMG. Regression analyses were performed on CI values and torque levels of elbow flexion, revealing a strong linear relationship. The slopes of regressions between SCI survivors and control subjects were compared. The findings indicated that the range of distribution of CI values and slopes was greater in subjects with SCI than in control subjects (p < 0.05). The increase or decrease in slope was also observed at the individual level. This suggests that the CI and its sEMG clustering-torque relation may serve as valuable quantitative indicators for determining neuromuscular lesions after SCI, contributing to the development of effective rehabilitation strategies for improving motor performance.

Електронне урядування як невід’ємний атрибут публічних комунікацій громадянського суспільства

Ukraine has identified the digital transformation of public communications as a priority policy for developing civil society. After the Association Agreement of Ukraine with the European Union, the introduction of European norms and standards in establishing electronic democracy as the basis for further developing the digital public space is of great importance. The study aims to justify measures to improve the mechanisms of civil society’s public communications in the conditions of electronic democracy in Ukraine, considering foreign experience. The content of the theoretical foundations of electronic governance in the context of functional support is disclosed; the level of information and communication technologies in the system of public management and administration was analyzed; the system of electronic government was investigated in the context of the development of public communications and the renewal of the regulatory and legal framework of Ukraine; trends of state policy in the field of e-governance were monitored; ways of further development of the information and digital space in the system of public communications of Ukraine are proposed. Based on the aspect analysis, a conceptual model of the system of information and communication provision of e-governance is proposed, which is built based on the analysis of the subject area and the selection of priority electronic resources that consider the interests of the state and individual subjects of civil society. In modern conditions, the system of electronic public communications must be fully adapted to the needs and requirements of civil society, in which modern information and communication technologies are the main driving forces of social and economic transformations. Information technology innovations in public administration must be complex, simultaneously, and coherently combining informational, organizational, legal, socio-psychological, personnel, technical, and other factors. Keywords: electronic governance, communications, information and communication technologies, public administration, civil society.

The Impact of Service Quality on Customer Satisfaction of BPJS Employment at The Mojokerto Branch Office

The quality of public services needs to be optimized in order to meet the expectations of service users and strengthen public trust in government institutions. Several indicators to measure the quality of public services include: tangible, reliability, responsiveness, assurance and empathy. The aim of the research is to examine in depth the quality of public services which have an impact on community satisfaction through a qualitative approach. This research was conducted at BPJS Employment Mojokerto branch office, East Java Province, Indonesia. Research sampling used snowball sampling where existing subjects provided references to recruit the required samples. In this technique an individual subject provides information about only one other subject and then the chain continues with only one reference from one subject. This pattern is continued until the subjects available as samples are deemed to have met the requirements. The research subjects are customers who intensively use BPJS Employment services. The results of this research conclude that the quality of service at BPJS Employment, including the dimensions of tangible, reliability, responsiveness, assurance and empathy, its implementation is in line with the expectations of service users so that they feel satisfied with the services provided by BPJS Employment Mojokerto.

Beyond symptom classification: Analyzing subjectivity of people diagnosed with obsessive compulsive disorder through Lacanian Discourse Analysis perspective

Intrusive thoughts and repetitive behaviors are manifested in numerous forms, however regarding the symptom-based system, people with such diverse forms of symptoms are diagnosed under the same category, named obsessive-compulsive disorder (OCD). The social constructivist approach, that have an increasingly substantial impact on psychotherapy research, emphasizes the subjectivity of individuals since the therapeutic field focuses on one-to-one work. Although studies on psychotherapy and the use of language are expanding, to the best knowledge of authors the subjectivity of people diagnosed with obsessive-compulsive disorder has not yet been studied using a combination of qualitative, discursive, critical, and language-based perspectives. The main purpose of this study was to critically evaluate the symptom-based diagnosis in the therapeutic process, with a particular emphasis on the subjectivity of people with OCD symptoms and their discursive practices. For this aim, interviews were conducted with six participants who were diagnosed with OCD and selected via the purposive sampling method. As for the qualitative analysis, critical and Lacanian Discourse Analysis perspectives were utilized. Considering the concepts of this perspective, the analysis revealed that though all participants were diagnosed under the same category, namely OCD, their basic signifiers, positioning, and relationships with the Other were quite distinct. Furthermore, differentiated patient discourses and gender differences emerged as crucial issues that were discussed in the light of Lacanian psychoanalytic literature. These findings suggested that individuals should be carefully listened to within their own subjectivity and psychological structures instead of being broadly categorized on the basis of symptom similarity. Based on the findings, the current study presents a diagnostic debate and key clinical implications.

UGDYMAS TVARIAM VYSTYMUISI PRADINĖJE MOKYKLOJE: BŪSIMŲJŲ PRADINIŲ KLASIŲ MOKYTOJŲ POZICIJA

The results of the survey showed that a large proportion of pre-service teachers, when assessing the situation over the next 10 years in nine key areas (air pollution, deforestation, biotic crisis, greenhouse effect, water scarcity, radioactive waste, GMOs, water pollution, global warming), predicted that the situation would worsen in all areas. It is clear that such scenarios are mostly dependent on the socio-economic development of humanity and what measures/actions will be taken at national and international level to minimise the consequences of such predictions for humanity. The results of the study show that in the national context, sprawl and solid waste are seen as the most pressing environmental problems. Endangered species, deforestation, exotic plants and/or animals are not considered to be a pressing issue in Lithuania. The vast majority of preservice teachers consider their knowledge of sustainable development to be insufficient and say that much more is needed. These findings oblige curriculum designers and implementers to take this into account when improving/restructuring/developing curricula and constructing the content of individual subjects. The results suggest that the majority of respondents consider teaching about sustainable development at an early age to be very important. The latter variable is directly correlated with the need for knowledge about sustainable development. Respondents who emphasise the importance of teaching about sustainable development have a correspondingly higher need for knowledge about sustainable development. In addition, it is found that the majority of the respondents have a positive attitude towards sustainable development and only a small number of respondents have a neutral attitude towards it. The study certainly has some limitations. Firstly, the sample size of the study is small, despite the fact that it is in principle in line with the requirements of a preliminary/pilot study. Due to the homogeneity of the population studied, possible gender differences were not analysed. Keywords: education for sustainable development (ESD), quantitative survey, primary school, pre-service teachers, sustainable development

Analyzing Lower Limb Dynamics in Human Gait Using Average Value-Based Technique

The motivation of this study is to develop effective and economical assistive technologies for people with physical disabilities. The novelty in this manuscript is the application of the average value-based technique to accurately represent the involved biomechanics of the lower limb joints during the human gait cycle. This mathematical formulation of lower limb joints’ biomechanics forms the first objective for modeling and final exoskeleton prototype development. To account for modeling the characteristics of human locomotion, the nth-order linear differential equation with constant coefficients is considered with appropriate modification. The physical characteristics of an individual are represented by the constant coefficients (P0, P1, P2, and P3) of the modified infinite series, which are obtained by processing experimental data collected using an optical technique. The differential terms of the infinite series are replaced by difference terms (δbavg, δ2bavg, and δ3bavg) since the data were captured as a set of digital values. The work presented here is based on the experimental results of individuals suitably categorized according to their physical nature like age and other physical structure. The optically monitored positional values of the lower limb joints of the individual subjects while they are completing the gait cycles are used for getting values of different terms of the model. The data collected through the conduct of experiments are used for finding the values of the terms of the differential equation. The model is effectively validated through experimental results. It was determined that the representation’s accuracy fell within the ±5% acceptable tolerance limit. The model is prepared for healthy as well as disabled persons, through which the disability is quantified. The resulting model can be used to develop assistive devices for people with physical disabilities. This results in the rehabilitation process and thereby helps the reintegration into society, subsequently allowing them to lead a normal life.

Learning Relational Categories: Benefits of Blocking, Classification, and Subject-Specific Examples

In order to make informed instructional decisions, teachers need psychological knowledge about relational categories. We conducted two 2 × 2 experiments to examine effective designs for learning relational categories in the context of teacher education. In both experiments, a blocked compared to an interleaved example format was more beneficial for learning relational categories when generating new examples. Experiment 1 ( N = 176) additionally showed that student teachers generated new examples more successfully when they had to classify rather than read examples. Moreover, Experiment 2 ( N = 95) revealed that student teachers who learned with examples taken from their individual subjects rather than examples from random subjects generated new examples more successfully. A mediation analysis showed that the subject-specific task value mediated the effect on example generation. The detrimental effects of an interleaved format could be partly compensated for by learning with subject-specific examples.