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423 results for “University students”
Improving Menstrual Health Through BCC Among Bangladeshi University Students
ClinicalTrials.gov study NCT07047222. IPD Sharing: YES. Countries: 1. Publications: 10.
Mindfulness in University Students. ATENEU Program
ClinicalTrials.gov study NCT05929430. IPD Sharing: NO. Countries: 1. Publications: 10.
Data from: Social determinants of food group consumption based on Mediterranean diet pyramid: a cross-sectional study of university students
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Grades of Computer Science Students in a Nigerian University
<p><strong>Brief Description of Dataset</strong></p> <p>The dataset contains information about students in a 5-year Bachelor of Technology Degree in Computer Science from a North Eastern Nigerian University of Technology. The year of enrolment of the students ranges from 2005 to 2015. In the dataset, “NA” means that the student did not attempt the course.</p> <p><strong>Data Cleaning</strong></p> <p>First steps: the student marks that are less than 40 are excluded, as the course has to be retaken to be passed with a minimum of 50 marks. In addition, courses that are taken outside of graduation audit by students are eliminated. </p> <p>There were 430 students screened for enrolment in the study with 95 being excluded because they did not take the course within the period of degree program for their early exemption. The exact ages of the participants are unknown other than all students enrolled were aged above 18 years of age.</p> <p> </p> <p> </p>
Data from: Characteristics of university students supported by counseling services: analysis of psychological tests and pulse rate variability
Objective <p>Mental health is an essential issue during adolescence. The number of students who use counseling services is increasing in universities. We attempted to confirm the characteristics of the students who access counseling services using both psychological tests and pulse rate variability (PRV) for better support for students' academic success.</p> Methods <p>We recruited the participants for this study from the students who had counseling sessions at Kanazawa University (Group S). As a control group, we also recruited students who had no experience in counseling services (Group H). We obtained health information from the database of annual health checkups. Participants received the Wechsler Adult Intelligence Scale (WAIS) III, Autism-Spectrum Quotient (AQ), Sukemune-Hiew (S-H) Resilience Test, and State-Trait Anxiety Inventory-JYZ (STAI). We also studied the SF-12v2 Health Survey. As a physiological test, we examined the spectral analyses of pulse rate variability (PRV) by accelerating plethysmography. We performed a linear analysis of PRV for LF, HF, and LF/HF as indexes of autonomic nervous function. We also conducted a non-linear analysis of PRV for the largest Lyapunov exponent (LLE). Additionally, we examined participants' blood for autoantibodies against glutamate decarboxylase (GAD) 65.</p> Results <p>A total of 105 students participated in this study. Group S had 37 participants (Male: 26, Female: 11), and Group H had 68 participants (Male: 27, Female 41). <a name="_Hlk24561145">There were five males and one female who had diagnoses of autism spectrum disorder (ASD), and three males and no female with attention deficit hyperactivity disorder (ADHD) by medical institutes in Group S. Additionally, four males and two females had diagnoses of ASD with ADHD by medical institutes in Group S.</a> A male with ASD in Group S had epilepsy. The students of Group S had characteristics as follows: 1) lower power of WMI despite high Full-Scale IQ, 2) higher ASD traits especially in Male, 3) lower resilience powers, 4) higher anxiety trait, 5) lower QOL in Role/social component in both Male and Female, 6) lower QOL in Mental component in Male 7) shifting of autonomic nervous balance toward higher sympathetic activity.</p> Conclusion <p>We could confirm the characteristics of students who visited counseling rooms for mental support. We also found gender differences in specificities of Group S. The educational system is changing rapidly to adjust social requests. These changes make conflict with the features of students of Group S. We should think about appropriate supports for the students who would pioneer the future of humanity.</p>
data set related to article Coping Power Universal for middle school students: The first efficacy study
<p>This record contains raw data related to article Coping Power Universal for middle school students: The first efficacy study</p>
Student oriented subset of the Open University Learning Analytics dataset
<p>The Open University (OU) dataset is an open database containing student demographic and click-stream interaction with the virtual learning platform. The available data are structured in different CSV files. You can find more information about the original dataset at the following link: <a href="https://analyse.kmi.open.ac.uk/open_dataset">https://analyse.kmi.open.ac.uk/open_dataset</a>.</p> <p>We extracted a subset of the original dataset that focuses on student information. 25,819 records were collected referring to a specific student, course and semester. Each record is described by the following 20 attributes: <em> code_module, code_presentation, gender, highest_education, imd_band, age_band, num_of_prev_attempts, studies_credits, disability, resource, homepage, forum, glossary, outcontent, subpage, url, outcollaborate, quiz, AvgScore, count</em>.<br> <br> Two target classes were considered, namely Fail and Pass, combining the original four classes (Fail and Withdrawn and Pass and Distinction, respectively). The final_result attribute contains the target values.<br> <br> All features have been converted to numbers for automatic processing.<br> <br> Below is the mapping used to convert categorical values to numeric:</p> <ul> <li>code_module: 'AAA'=0, 'BBB'=1, 'CCC'=2, 'DDD'=3, 'EEE'=4, 'FFF'=5, 'GGG'=6</li> <li>code_presentation: '2013B'=0, '2013J'=1, '2014B'=2, '2014J'=3</li> <li>gender: 'F'=0, 'M'=1</li> <li>highest_education: 'No_Formal_quals'=0, 'Post_Graduate_Qualification'=1, 'HE_Qualification'=2, 'Lower_Than_A_Level'=3, 'A_level_or_Equivalent'=4</li> <li>IMBD_band: 'unknown'=0, 'between_0_and_10_percent'=1, 'between_10_and_20_percent'=2, 'between_20_and_30_percent'=3, 'between_30_and_40_percent'=4, 'between_40_and_50_percent'=5, 'between_50_and_60_percent'=6, 'between_60_and_70_percent'=7, 'between_70_and_80_percent'=8, 'between_80_and_90_percent'=9, 'between_90_and_100_percent'=10</li> <li>age_band: 'between_0_and_35'=0, 'between_35_and_55'=1, 'higher_than_55'=2</li> <li>disability: 'N'=0, 'Y'=1</li> <li>student's outcome: 'Fail'=0, 'Pass'=1</li> </ul> <p>For more detailed information, please refer to:</p> <p><br> Casalino G., Castellano G., Vessio G. (2021) Exploiting Time in Adaptive Learning from Educational Data. In: Agrati L.S. et al. (eds) Bridges and Mediation in Higher Distance Education. HELMeTO 2020. Communications in Computer and Information Science, vol 1344. Springer, Cham. <a href="https://www.google.com/url?q=https%3A%2F%2Fdoi.org%2F10.1007%2F978-3-030-67435-9_1&sa=D&sntz=1&usg=AFQjCNF7fUT9S4TcSpImSr4e_DjaLn3wtg">https://doi.org/10.1007/978-3-030-67435-9_1</a></p>
Data on universities offering undergraduate degrees that train students for soil science careers at universities in the USA and its territories
<p>Several soil science education studies over the last 15 years have focused on the number of students enrolled in soil science programs. However, no studies have quantitatively addressed the number of undergraduate soil science preparatory programs that exist in the United States, which means we do not have solid data concerning whether overall program numbers are declining, rising, or holding steady. This also means we do not have complete data on the same trends for total undergraduate soil science students in the United States. This study used the US Office of Personnel Management (OPM) Soil Science Series 0470 standards to determine if a bachelor's degree met soil science preparatory criteria. Lists of the approximately 3,500 regionally accredited colleges and universities were obtained from the regional accrediting agencies and the website of each of the colleges and universities was visited to determine if they had a degree program that met the OPM 0470 criteria. A total of 92 soil science preparatory degree programs were identified at 86 colleges and universities. These programs were primarily linked to 1) agriculture, 2) environmental science, and 3) soil and water science based on number of degree occurrences. This study creates a baseline for future studies that can investigate trends in soil science programs. It also provides insight into the institutions and degree programs that should be included in soil science education studies.</p>
Factors associated with Depression: Insights from a cross–sectional study among University students in Vietnam
<p>This is the supportive data for research on depression in Vietnamese Student</p>
An Assessment of University Students' Perception Towards the Adoption and Use of Mobile Learning Technologies for Learning
<p>Mobile learning technologies serve has as a transformative tool in the educational sector which gives room for accessibility, flexibility and scalability. It also improves student learning outcomes. This study aims to review research on students' attitude and perception towards the adoption and implementation of mobile learning technologies using the Unified Theory and Acceptance and Use of Technology (UTAUT) model. From the studies, results showed that students' perception has a major impact on the adoption and use of mobile technologies. However, based on the various literature reviewed, students' perception is influenced by performance expectancy, effort expectancy (ease of use of the technology), social influence, perceived enjoyment and satisfaction. All these must be put into consideration before design and implementation for the effectiveness. Nevertheless, if all or some of these constructs were not incorporated in the development of mobile learning technology, obstructs the adoption and implementation of mobile learning.</p>
An Assessment of University Students' Perception Towards the Adoption and Use of Mobile Learning Technologies for Learning
<p>Mobile learning technologies serve has as a transformative tool in the educational sector which gives room for accessibility, flexibility and scalability. It also improves student learning outcomes. This study aims to review research on students' attitude and perception towards the adoption and implementation of mobile learning technologies using the Unified Theory and Acceptance and Use of Technology (UTAUT) model. From the studies, results showed that students' perception has a major impact on the adoption and use of mobile technologies. However, based on the various literature reviewed, students' perception is influenced by performance expectancy, effort expectancy (ease of use of the technology), social influence, perceived enjoyment and satisfaction. All these must be put into consideration before design and implementation for the effectiveness. Nevertheless, if all or some of these constructs were not incorporated in the development of mobile learning technology, obstructs the adoption and implementation of mobile learning.</p>
Relationship between academic stress, emotional intelligence and eating behavior in university students
<p>Emotional intelligence refers to the group of capabilities that enable people to regulate mood and feelings, especially the perception of stress. Although the reasons are not fully understood, there is a link between stress, eating behavior, and emotional intelligence. Our objective was to relate emotional intelligence, academic stress, and eating behavior among Psychology and Biology students at the University of Panama. We determined the association between academic stress, clarity, attention, and emotional repair scores, as well as eating habits at the beginning and end of the semester.</p> <p>Compared to psychology students, biology students feel more academic stress. Psychology students have greater emotional clarity and attentiveness. There is no association between perceived stress, emotional intelligence, and eating behavior. We recommend incorporating physiological variables and instruments that assess the concept of emotional eating.</p> <p>This file includes the coding of the variables, as well as the scores obtained by each participant.</p>
Data base eating disorder and irritable bowel syndrom university students
<p>eating disorder and irritable bowel syndrom among university students in Rouen (France)</p> <p>Associated behaviors</p>
In 2017, Plantix, a free smartphone app that helps identify plant damage, was introduced to the Indian state of Andhra Pradesh, with an extension partner. Plantix was created by Progressive Environmental and Agricultural Technologies (PEAT), a German startup. Two PEAT cofounders, Charlotte Schuman (second from the right) and Alex Kennepohl (center, with eyeglasses), confer about the smartphone app with students from Angrau University. Farmers and gardeners can transmit their plant images to Plantix, which uses deep learning and computer vision to help identify diseases and pests. The smartphone app offers symptom descriptions, treatment recommendations, and potential preventive actions. Photographs: Courtesy of PEAT GmbH. in Deep learning brings speed, accuracy to the life sciences.
In 2017, Plantix, a free smartphone app that helps identify plant damage, was introduced to the Indian state of Andhra Pradesh, with an extension partner. Plantix was created by Progressive Environmental and Agricultural Technologies (PEAT), a German startup. Two PEAT cofounders, Charlotte Schuman (second from the right) and Alex Kennepohl (center, with eyeglasses), confer about the smartphone app with students from Angrau University. Farmers and gardeners can transmit their plant images to Plantix, which uses deep learning and computer vision to help identify diseases and pests. The smartphone app offers symptom descriptions, treatment recommendations, and potential preventive actions. Photographs: Courtesy of PEAT GmbH.
Emotional Intelligence and Authentic Leadership. A comparative study of university students in Chile, Spain, and Mexico.
<pre><span>Research database titled: </span><strong><span>Emotional Intelligence and Authentic Leadership. A comparative study of university students in Chile, Spain, and Mexico.</span></strong></pre> <pre></pre>
DATA SET: Perceived instructor's emotional support as a predictor of college students' academic resilience in a Philippine university landscape: From the perspectives of Resilience and Self-Determination Theory
<p>Data from: Perceived instructor’s emotional support as a predictor of college students’ academic resilience in a Philippine university landscape: From the perspectives of Resilience and Self-Determination Theory by Lobo et al. (2024).</p>
Intention to use Mobile Learning APPs in university students
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Evaluating the Impact of Education on Sustainability Knowledge, Attitudes, and Intentions Among University Students
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Knowledge, attitudes, and practices towards human papillomavirus infection and vaccination: a cross-sectional study among university students in Astana, Kazakhstan. Dataset
<p>Dataset and code book for the study entitled <strong>Knowledge, attitudes, and practices towards human papillomavirus infection and vaccination: a cross-sectional study among university students in Astana, Kazakhstan.</strong></p>
Adaptation and evolution of teaching method for university programming subject to the online learning environment - Student surveys dataset
<p>This dataset contains anonymized survey data of students studying Operating Systems class at the Technical University of Košice in the span of school years 2017/2018 to 2020/2021.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.