Browse
Submit Data
Databases
API
Help

Dataset Information

6 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Students home alone—profiles of internal and external conditions associated with mathematics learning from home

ABSTRACT: Abstracts This study aims at describing differences in internal and external resources of students to handle mathematics learning from home. Based on data from N = 223 7th-grade secondary school students gathered via an online survey at the end of the first school year during the COVID-19 pandemic, we used latent profile analysis to identify student profiles defined by the internal factors perceived value and success of students’ math learning from home and the external factors family support and teacher support—all specifically related to home learning. A number of general learning conditions, comprising internal (e.g., sustained attention) and external factors (e.g., socioeconomic status), are included as outcome variables. The best-fitting four-profile solution suggests one profile with comparably unfavorable internal and external resources. About 35% of the students are assigned to that profile. The other three profiles show combinations of, relative to the sample, more and less promising specific home learning and general learning conditions suggesting that these students have different resources available in the face of learning mathematics from home.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10212-021-00590-w.

SUBMITTER: Hofer S

PROVIDER: S-EPMC8727485 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Digital support principles for sustained mathematics learning in disadvantaged students.

Project description:This study addresses the pressing issue of how to raise the performance of disadvantaged students in mathematics. We combined established findings on effective instruction with emerging research addressing the specific needs of disadvantaged students. A sample of N = 260 disadvantaged 6th-graders received 4 weeks (15 lessons) of fraction instruction either as usual or evidence-based instruction, with and without digital learning support (i.e., interactivity, adaptivity, and immediate explanatory feedback). To examine the sustainability of effects, we assessed students' fraction knowledge immediately after the 4 weeks and once again after a period of additional 8 weeks. Generalized linear mixed models revealed that students only benefitted from evidence-based instruction if digital support was available in addition. Digital support principles implemented in evidence-based instruction helped disadvantaged students to acquire mathematics knowledge-and to maintain this knowledge.

| S-EPMC7584209 | biostudies-literature

Contrasting Profiles of Low-Performing Mathematics Students in Public and Private Schools in the Philippines: Insights from Machine Learning.

Project description:Filipino students performed poorly in the 2018 Programme for International Student Assessment (PISA) mathematics assessment, with more than 50% obtaining scores below the lowest proficiency level. Students from public schools also performed worse compared to their private school counterparts. We used machine learning approaches, specifically binary classification methods, to model the variables that best identified the poor performing students (below Level 1) vs. better performing students (Levels 1 to 6) using the PISA data from a nationally representative sample of 15-year-old Filipino students. We analyzed data from students in private and public schools separately. Several binary classification methods were applied, and the best classification model for both private and public school groups was the Random Forest classifier. The ten variables with the highest impact on the model were identified for the private and public school groups. Five variables were similarly important in the private and public school models. However, there were other distinct variables that relate to students' motivations, family and school experiences that were important in identifying the poor performing students in each school type. The results are discussed in relation to the social and social cognitive experiences of students that relate to socioeconomic contexts that differ between public and private schools.

| S-EPMC9504801 | biostudies-literature

Exploration of the external and internal factors that affected learning effectiveness for the students: a questionnaire survey

Project description:Learning effectiveness may be affected by internal and external factors, including personal attitude, motivations, learning skills, learning environment and peer pressure. This study sought to explore potential factors on students who majored in medical technology. The 106 students who completed their internship at Chang Gung Memorial Hospital were enrolled in this study. A written questionnaire was analyzed to explore the relationship between potential factors and learning effectiveness. The strength of relationship between the outcome and each factor was evaluated using Spearman correlation coefficients. A multiple linear regression model was constructed to assess how those factors affected learning effectiveness altogether. The results indicated that the learning effectiveness of the students mainly depended on three factors: the “extracurricular studies” and “willingness to cooperate” were positively associated with learning effectiveness. However, the “weakened motivation due to uncertainty” is negatively associated with learning effectiveness. We suggested that the educators can understand the uncertainty of students about the future. Additionally, the projects that require joint cooperation and discussion need to be given. The most important thing is that students should be able to integrate the learning content instead of rote. Supplementary Information The online version contains supplementary material available at 10.1186/s12909-023-04035-4.

| S-EPMC9868504 | biostudies-literature

External and internal factors influencing self-directed online learning of physiotherapy undergraduate students in Sweden: a qualitative study.

Project description:PurposeOnline courses have become common in health sciences education. This learning environment can be designed using different approaches to support student learning. To further develop online environment, it is important to understand how students perceive working and learning online. The aim of this study is to identify aspects influencing students' learning processes and their adaptation to self-directed learning online.MethodsThirty-four physiotherapy students with a mean age of 25 years (range, 21 to 34 years) participated. Qualitative content analysis and triangulation was used when investigating the students' self-reflections, written during a five week self-directed, problem-oriented online course.ResultsTwo categories emerged: 'the influence of the structured framework' and 'communication and interaction with teachers and peers.' The learning processes were influenced by external factors, e.g., a clear structure including a transparent alignment of assignments and assessment. Important challenges to over-come were primarily internal factors, e.g., low self-efficacy, difficulties to plan the work effectively and adapting to a new environment.ConclusionThe analyses reflected important perspectives targeting areas which enable further course development. The influences of external and internal factors on learning strategies and self-efficacy are important aspects to consider when designing online courses. Factors such as pedagogical design, clarity of purpose, goals, and guidelines were important as well as continuous opportunities for communication and collaboration. Further studies are needed to understand and scaffold the motivational factors among students with low self-efficacy.

| S-EPMC4536344 | biostudies-literature

Longitudinal Trajectories of Reading and Mathematics Achievement for Students With Learning Disabilities.

Project description:We examined to what extent subgroups of students identified with learning disabilities (LDs; N = 630) in the Early Childhood Longitudinal Study, Kindergarten Class of 1998 to 1999 (ECLS-K): 1998 national longitudinal study displayed heterogeneity in longitudinal profiles of reading and mathematics achievement from first to eighth grades. Multivariate growth mixture modeling yielded four classes of combined reading and mathematics trajectories for students with LD. The largest class of students with LD (Class 2, 54.3%) showed mean T-scores for both achievement domains that averaged about 1 SD below the mean, with modest decline over time. Almost a quarter of the sample (Class 1, 22.3%) displayed mean T-scores in both achievement areas near the peer-normed average; these students were mostly White, from higher socioeconomic status (SES) backgrounds, and had experienced earlier identification as having an LD as well as shorter duration of LD service. Classifying heterogeneity in longitudinal trajectories of both achievement areas shows promise to better understand the educational needs of students identified with an LD.

| S-EPMC9939928 | biostudies-literature

Students' Motivation and Affection Profiles and Their Relation to Mathematics Achievement, Persistence, and Behaviors.

Project description:ObjectiveWe aimed to explore profiles of subgroups of United States students based on their motivational and affective characteristics and investigate the differences in math-related behaviors, persistence, and math achievement across profiles.MethodWe used 1,464 United States students (male 743 51%, female 721 49%, age 15.82 ± 0.28) from PISA 2012 United States data in our study. First, we employed latent profile analysis and secondary clustering to identify subgroups of students based on motivational (math self-concept, interest in math, perceived control, and instrumental motivation) and affective factors (math anxiety). Next, we used regression to compare differences in math behavior, persistence, and achievement among all identified subgroups.ResultsWe found five distinct groups of students with different patterns of motivation and affection. The subgroup of students with the lowest math anxiety and the highest motivation levels showed the highest math achievement and levels of persistence. The groups with high math interest, math self-concept, and instrumental motivation showed the most frequent math-related behaviors.ConclusionsOur findings reveal the complexity of the students' motivational and affective profiles. Our findings are significant for teachers and educators to understand the diversity of students and provide theoretical and practical support for individualized and differentiated instruction.

| S-EPMC7841336 | biostudies-literature

Data on students' learning experiences in mathematics during the COVID-19 school closure.

Project description:Like in other education systems around the world, the COVID-19 school closure in Zambia necessitated a shift from physical classroom face-to-face interactions to remote learning. However, it was not clear whether all students' remained engaged with the learning of mathematics during that time. The data described in this paper were collected to support the findings of a descriptive survey that aimed at finding out Zambian students' experiences with mathematics remote learning. A semi-structured questionnaire was used to collect data from 367 secondary school students in Kitwe district. It was anticipated that the collected information could provide some valuable insights into remote learning experiences among secondary school students in times of a crisis such as the COVID-19 outbreak and beyond.

| S-EPMC8601959 | biostudies-literature

Prefrontal Cortex Networks Shift from External to Internal Modes during Learning.

Project description:As we learn about items in our environment, their neural representations become increasingly enriched with our acquired knowledge. But there is little understanding of how network dynamics and neural processing related to external information changes as it becomes laden with "internal" memories. We sampled spiking and local field potential activity simultaneously from multiple sites in the lateral prefrontal cortex (PFC) and the hippocampus (HPC)-regions critical for sensory associations-of monkeys performing an object paired-associate learning task. We found that in the PFC, evoked potentials to, and neural information about, external sensory stimulation decreased while induced beta-band (?11-27 Hz) oscillatory power and synchrony associated with "top-down" or internal processing increased. By contrast, the HPC showed little evidence of learning-related changes in either spiking activity or network dynamics. The results suggest that during associative learning, PFC networks shift their resources from external to internal processing.As we learn about items in our environment, their representations in our brain become increasingly enriched with our acquired "top-down" knowledge. We found that in the prefrontal cortex, but not the hippocampus, processing of external sensory inputs decreased while internal network dynamics related to top-down processing increased. The results suggest that during learning, prefrontal cortex networks shift their resources from external (sensory) to internal (memory) processing.

| S-EPMC5039250 | biostudies-literature

Students' experiences with remote learning during the COVID-19 school closure: implications for mathematics education.

Project description:This paper reports the findings of a descriptive survey research that explored secondary school students' experiences with mathematics remote learning during the Corona Virus Disease 2019 (COVID-19) school closure. The study involved 367 students of ages 13 to 21 selected from six secondary schools in Kitwe district of Zambia using the cluster random sampling method. Using a mixed-methods research approach, quantitative and qualitative data were merged to provide a comprehensive analysis of the main findings in the context of the existing literature, the government's response to COVID-19 school closure, and the challenges associated with remote learning during that time. Research findings show that more than 56% of the respondents did not have sufficient access to Information and Communication Technologies (ICT), electricity, and internet services. Most of these respondents also held a belief that mathematics is a subject that is best learned with face-to-face interactions between the teacher and students, and among students. These results suggest a need for the education systems in Zambia and other similar contexts to put up infrastructure that supports the blended and online learning models during and after the COVID-19 pandemic.

| S-EPMC8287231 | biostudies-literature

Severe Pandemic Learning Loss and the Promise of Remotely Delivered Intervention in Students With Comorbid Reading and Mathematics Learning Difficulty.

Project description:Analyses were conducted with second graders, drawn from an ongoing multi-cohort randomized controlled trial (RCT), who had been identified for RCT entry based on comorbid reading comprehension and word-problem solving difficulty. To estimate pandemic learning loss, we contrasted fall performance for 3 cohorts: fall of 2019 (pre-pandemic; n = 47), 2020 (early pandemic, when performance was affected by the truncated preceding school year; n = 35), and 2021 (later pandemic, when performance was affected by the truncated 2019 to 2020 school year plus the subsequent year's ongoing interruptions; n = 75). Across the 2 years, declines (standard deviations below expected growth) were approximately 3 times larger than those reported for the general population and for students in high-poverty schools. To estimate the promise of structured remote intervention for addressing such learning loss during extended school closures, we contrasted effects in the RCT's 2018 to 2019 cohort (entirely in-person intervention delivery; n = 66) against the same intervention's effects in the 2020 to 2021 cohort (alternating periods of remote and in-person delivery; n = 29). Large intervention effects were not moderated by pandemic status, suggesting potential for structured remote intervention to address student needs during extended school closures.

| S-EPMC10201276 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data