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Supplements and underlying data for the study: Using Health Claims to Teach Evidence-Based Practice to Healthcare Students: A Mixed Methods Study
<p>Supplements and English translation of the Norwegian data sets, in addition to checklists for the manuscript.</p>
Impostor Syndrome in Final Year Computer Science Students: An Eye Tracking and Biometrics Study
<p>These are the artifacts that are associated with the paper: <strong>Impostor Syndrome in Final Year Computer Science Students: An Eye Tracking and Biometrics Study</strong></p> <p>This paper was accepted for publication at the 18th International Conference on Augmented Cognition</p> <p>The preprint of the paper is available at: https://arxiv.org/abs/2404.10194</p>
List of STEAM interventions for Students with Disabilities (SWDs) from 2013-2023
<p>List of Science, Technology, Engineering, the Arts and Mathematics (STEAM) interventions for Students with Disabilities (SWDs) from Early Childhood to Tertiary Education. This list was constructed for a systematic literature review (SLR) of educational interventions and strategies for SWDs from 2013-2023. The list contains the authors, the disability or disorder addressed, the STEAM area, the research approach, participants/educational level, learning outcomes, and conclusions. </p>
SelfCode 2.0: Annotated Corpus of Student Self-Explanations to Introductory JAVA Programs in Computer Science
<p><strong>Dataset Description:</strong> This dataset was collected during a lab study conducted in Spring 2022 for introductory JAVA programming. Students had to provide line by explanations to four JAVA programs in the experimental condition of the study. The JAVA Programs were selected from the examples made available in the <a title="PCEX" href="https://dl.acm.org/doi/abs/10.1145/3279720.3279726" target="_blank" rel="noopener">PCEX Worked Examples interface</a>. The explanations collected were then split by the number of attempts. Students could attempt twice based on the feedback provided using the the PCEX interface and in their third attempt they filled in the blanks to complete an explanation to the particular line of code. In this dataset, we only have the annotated examples of explanations provided by students. The explanations were annotated on their correctness (binary rating 0 or 1), completeness (binary rating 0 or 1) and similarity (rating scale 1 to 5).</p> <p><strong>Correctness:</strong> Given the line of code and context of the line in the program, if the student explanation covers **only** the topics relevant to the line of code</p> <p><strong>Completeness:</strong> Given the line of code and context of the line in the program, if the student explanation covers **all** the topics relevant to the line of code</p> <p><strong>Similarity:</strong> Given the line of code, the context of the line in the program and an expert explanation to the line of code, the metric compares the similarity on a rating scale from 1 to 5, defined in the following manner:</p> <p>1 - expert and student explanations are very different,</p> <p>2 -- expert and student explanations are somewhat alike, but there are major differences in the concepts / topics explained</p> <p>3 -- expert and student explanations are similar but there are differences in the concepts / topics explained</p> <p>4 -- expert and student explanations are similar and have few differences in the concepts / topics explained</p> <p>5 -- expert and student explanations are very similar.</p> <p> </p> <p>Overall 3000 single attempts (corresponding to 40 student explanation submission) were annotated against different various expert explanation pairs.</p> <p> </p> <p><strong>Dataset Summary:</strong></p> <p><strong>Explanation Type N Definition<br></strong>Experts 2 Source Code Line-by-Line Explanations by Experts<strong><br></strong>Students 60 (annotated 40) Source Code Line-by-Line Explanations by Students</p> <table> <tbody> <tr> <td>COUNT of std_sent_count</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>std_sent_count</td> <td>1</td> <td>2</td> <td>3</td> <td>4</td> <td>5</td> <td>6</td> <td>Grand Total</td> </tr> <tr> <td>1</td> <td>1854</td> <td>367</td> <td>245</td> <td>107</td> <td>34</td> <td>33</td> <td>2640</td> </tr> <tr> <td>2</td> <td>222</td> <td>46</td> <td>40</td> <td>12</td> <td>6</td> <td>6</td> <td>332</td> </tr> <tr> <td>3</td> <td>21</td> <td>5</td> <td>5</td> <td>5</td> <td>1</td> <td>2</td> <td>39</td> </tr> <tr> <td>4</td> <td>2</td> <td>1</td> <td>2</td> <td>3</td> <td> </td> <td> </td> <td>8</td> </tr> <tr> <td>Grand Total</td> <td>2099</td> <td>419</td> <td>292</td> <td>127</td> <td>41</td> <td>41</td> <td>3019</td> </tr> </tbody> </table> <p> </p> <p><strong>Sample Data:</strong></p> <p><strong>Program:</strong> PointTester; Line number: 12; Line code: private int y;<br><strong>Expert1: </strong>Every object of the Point class will have its own y-coordinate. Therefore, we<br>need to declare an instance variable for the class to store the y-coordinate of the point.<br>We declare it as int because we want to have integer coordinates for the point. Note<br>that an instance variable is a variable defined in a class, for which each instantiated<br>object of the class has a separate copy, or instance.<br><strong>Expert2:</strong> The instance variables are declared as private to prevent direct access to<br>them from outside the class. In this way, no unexpected modifications to a Point<br>object’s data are possible.<br><strong>Student1: </strong>initialize a private value inside the point class with no value yet<br><strong>Student2:</strong> Declares the private int variable y.<br><strong>Student3: </strong>Creates a private int that can only be accessed by class Point called int y<br>...<br><strong>Student59:</strong> private variable used to store the value entered into the value of the y<br>coordinate</p> <p> </p> <p><strong>Kappa Scores:</strong></p> <div> <table> <tbody> <tr> <td> <p>Round</p> </td> <td> <p>Row Numbers</p> </td> <td> <p>Correctness Rating Agreement %age</p> </td> <td> <p>Correctness Rating Kappa</p> </td> <td> <p>Sufficiency Rating Agreement %age</p> </td> <td> <p>Sufficiency Rating Kappa</p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>1000 - 1432 </p> </td> <td> <p>92.9</p> </td> <td> <p>0.365</p> </td> <td> <p>0.708</p> </td> <td> <p>-0.0123</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>1432 - 1864</p> </td> <td> <p>94.2</p> </td> <td> <p>0.263</p> </td> <td> <p>77.6</p> </td> <td> <p>0.329</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>1864 – 1964 </p> </td> <td> <p>75.3</p> </td> <td> <p>0</p> </td> <td> <p>70.3</p> </td> <td> <p>0.299</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>1964 -- 2064 </p> </td> <td> <p>86</p> </td> <td> <p>0.108</p> </td> <td> <p>74.7</p> </td> <td> <p>0.275</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p>2064 – 2264</p> </td> <td> <p>95.5</p> </td> <td> <p>-0.0158</p> </td> <td> <p>81.5</p> </td> <td> <p>0.312</p> </td> </tr> <tr> <td> <p>6</p> </td> <td> <p>2264 – 2464</p> </td> <td> <p>83.5</p> </td> <td> <p>0.039</p> </td> <td> <p>86.5</p> </td> <td> <p>0.648</p> </td> </tr> <tr> <td> <p>7</p> </td> <td> <p>2464 – 2864</p> </td> <td> <p>92</p> </td> <td> <p>0.103</p> </td> <td> <p>74.5</p> </td> <td> <p>0.188</p> </td> </tr> <tr> <td> <p>8</p> </td> <td> <p>2864 -- 3005</p> </td> <td> <p>86.5</p> </td> <td> <p>-0.026</p> </td> <td> <p>72.3</p> </td> <td> <p>0.117</p> </td> </tr> </tbody> </table> </div> <p> </p> <p> </p> <p><strong>Citation Format:</strong><br>If using this dataset in your project please cite:</p> <p>Lekshmi-Narayanan, A.-B., Chapagain, J., Brusilovsky, P., & Rus, V. (2023). SelfCode 2.0: Annotated Corpus of Student Self-Explanations to Introductory JAVA Programs in Computer Science [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10912669</p> <p><strong>Acknowledgements:</strong><br>This project was funded as a part of the NSF AWARD # 1822752</p> <p> </p> <p> </p>
Data from: Redesign of a life cycle figure improves student conceptions of ecology and evolution
<p>Life cycle diagrams communicate the developmental life stages of an organism. Design choices may inadvertently communicate additional information about survivorship rates, genetic variation, and microevolutionary change. In this controlled experiment, we randomly assigned one of three life cycle diagrams to 684 college students. Each figure included identical life stages of a fictitious organism's development but differed in 1) number of offspring (single or multiple) and 2) layout (cyclical or linear). Each participant could reference the figure when answering questions about organism survival, variation among offspring, and variation between generations. Students scored 21–37% higher on questions about survivorship when the available diagram included multiple offspring. Students scored 19–30% higher on questions about microevolution when the diagram layout was linear. Overall, students who received the figure with a linear layout and multiple offspring earned the highest average score (54.5%, or 3.3 of 6 questions) on the assessment, while students with the traditional figure (cyclical layout with single offspring) scored the lowest average (26.1%, or 1.6 of 6 questions). These results suggest that figure design affects student interpretations and may assist student learning about ecology and evolution concepts and common misconceptions.</p>
DIDACTIC STRATEGY BASED ON EXELEARNING FOR THE DEVELOPMENT OF PEDAGOGICAL SKILLS IN BIOTECHNOLOGY STUDENTS - DIAGNOSIS
<p>Los datos corresponden al diagnóstico realizado a estudiantes a través de un cuestionario, en una investigación para la elaboración de una estrategia didáctica basada en ExeLearning</p>
Additional Material for: Debiasing Architectural Decision-Making: An Experiment With Students and Practitioners
<p>Additional Material for: Debiasing Architectural Decision-Making: An Experiment With Students and Practitioners submitted to ICSA 2025.<br><br>The files contain:<br>1. README.md - A short file describing the contents of the replication package.<br>2. Coding guide.docx - a guide used for coding, with examples from the experiment's participants.<br>3. Coding_results.xlsx - data with all measurements for all participants.<br>4. Questionnaire.xlsx - questionnaire used to gather demographic participant's data.<br>5. Experiment-plan.docx - the detailed plan of all the experiment steps.<br>6. Debiasing-workshop-slides.pptx - slides used during the debiasing workshop.<br>7. Debiasing-workshop-plan.docx - a detailed plan of the debiasing workshop, explaining how exactly the debiasing presentation should be used.<br>8. Consent_form.docx - a consent form that was signed by the participants from one of the author's countries, where guidelines suggested the use of gathering additional written consent.<br><br></p>
Molar-incisor hypomineralization: Knowledge and perception of Syrian undergraduate and postgraduate dental students
<p>Dataset for all analyses</p>
Remote learning and students' mental health during the Covid‑19 pandemic: Dataset and questionnaire
<p>Questionnarie and dataset for the article "Remote learning and students' mental health during the Covid‑19 pandemic: A mixed method enquiry", published in "Prospects" (2021, <a href="https://doi.org/10.1007/s11125-020-09530-w">https://doi.org/10.1007/s11125-020-09530-w</a>) </p>
Impact of Motivation, Learning Strategy and Intelligence Quotient on Medical Students Grades during first semester
<p>Rekapitulasi data MSLQ dan IQ </p>
THE IMPACT OF NUTRITION ON STUDENT PERFORMANCE AND HEALTH: WHY THE MEDITERRANEAN DIET?
<p>Malnutrition is associated with poor psycho-physical health, behavioral problems, and unsatisfactory learning outcomes. Numerous studies show that adhering to a healthy diet such as the Mediterranean Diet (MD) can have beneficial effects on students, increasing their academic performance, quality of life, and their health status. 200 students aged 10-15 years it turns out that a large proportion of students surveyed; despite the information they have about healthy foods, do not eat properly and have admitted that they have low concentration and lack of attention during the learning process. Based on this identified situation, it is necessary to orient students towards a correct lifestyle and mainly towards the Mediterranean diet as a healthy dietary model.</p>
Assessment of entrepreneurial competences of Industrial Engineering Students: Post-COVID19 results
<p>The file contained are results of the research on the Entrepreneurial Competences of Industrial Engineering students at the University of Novi Sad. The research is conducted in the course of Reliability of Technical Systems and Maintenance. The students are enrolled in the 3rd graduate year at the module Industrial Engineering. The study is conducted during the winter semester of 2021-2022. The study explores entrepreneurial competences by using the EntreComp Reference Framework as a research instrument. The dataset contains students' responses, Fold change, Wilcoxon rank test and PLS-DA statistical test analysis. In addition, all three analysis included contain graphs and plots included, VIP plot and analysis and associated results. The writting of the study is performed during April of 2022.</p>
Let's save the kingdom! The impact of gamification on flow and academic achievement in secondary school students
<p>Datos del Flow</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 from: The Effect of Watching Lecture Videos at 2x Speed on Memory Retention Performance of Medical Students: An Experimental Study
<p><strong>The study is accesible from here: </strong><a href="https://www.tandfonline.com/doi/full/10.1080/0142159X.2023.2189537">https://www.tandfonline.com/doi/full/10.1080/0142159X.2023.2189537</a><br> <br> <strong>Dataset Info</strong></p> <p># The first row of the dataset identifies the columns.<br> # The first column represents the participant ids.<br> # The second column represents the participants' universities (1 to 9 represent nine universities).<br> # The third column represents the years of participants in their six-year-long medical schools (1: Year-1 students, 2: Year-2 students).<br> # The fourth column represents the genders of participants (1: Female, 2: Male).<br> # The fifth column represents the speed that participants watched the video at (1: 1x Speed, 2: 2x Speed).<br> # The sixth to the twenty fifth columns (i_q1 to i_q20) represent the scores in the first to twentieth questions in the Immediate test, respectively (0: False, 1: True).<br> # The twenty sixth column (i_totalscore) represents the total score in the Immediate test.<br> # The twenty seventh to fourty sixth columns (d_q1 to d_q20) represent the scores in the first to twentieth questions in the Delayed test, respectively (0: False, 1: True).<br> # The fourty seventh column (d_totalscore) represents the total score in the Delayed test.</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.
Determining Factors Influencing Pre-Service ELT Students' Behavioral intention to Use ChatGPT in Türkiye
<p>This dataset is collected for the study entitled: " Determining Factors Influencing Pre-service ELT Students's Behavioral intention to Use Chat GPT in Türkiye." by Grassini & Köse collected during February & March, 2024. </p> <p> </p>
Therapeutic working alliance in brief therapy with college students: In-person versus telemental health
<p>This study compared the therapeutic working alliance in brief counseling using two delivery methods: synchronous video delivery and in-person delivery. The alliance was measured using the Working Alliance Inventory (client version). Participants were 49 undergraduate college students between the ages of 18 and 22. Solution-Focused Brief Therapy was the treatment protocol, and the study used a randomized, controlled design. Welch's t-tests and non-inferiority analyses were conducted, in addition to hierarchical regression analyses to examine the predictive value of the working alliance on post-treatment anxiety. Non-inferiority statistical analyses indicated that there was no statistically significant difference in working alliance for online delivery compared to in-person. A hierarchical regression anaIysis suggests that the therapeutic working alliance contributed to anxiety treatment outcomes for college student participants.</p>
The Role of Self-Control, Authoritarian Parenting Style with Cyberbullying Behavior among Junior High School Students
<p>This data pertains to a study titled "The Role of Self-Control, Authoritarian Parenting Style with Cyberbullying Behavior among Junior High School Students." The study involved 539 junior high school students aged 13 to 15 years, selected from three private schools in Yogyakarta, Indonesia using purposive sampling. Utilizing a quantitative approach, data were gathered using the Cyberbullying Scale, Self-Control Scale, and Authoritarian Parenting Scale.</p>
ScienceDex guides
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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.