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31 results for “MOOCs”
Massive Open Online Courses(MOOCs) and why they fail. A case of HarvardX
<p>Massive open online courses (MOOCs) are free online courses open for everyone to enroll. MOOCs are attractive because they attempt to level the playing field and provide opportunities for students from all walks of life and from different countries to study "together" at the comfort of their own homes and this is facilitated by leading professors from renowned universities at little to no cost. They are sold as an on-demand online education to accommodate conflicting family and work responsibilities which offer students the flexibility to study and do life. Schools like University of Maryland University College were among the first universities to accept MOOCs for credit, since then more institutions have welcomed the idea of providing online education for free. MOOCs sadly have simply not lived up to their mission to transform the educational system around the world and once again we see how a good free initiative fails.<br> <br> Despite of the popularity of MOOCs, employers do not regard certifications from MOOCs as valid credentials neither as an alternative to traditional educational institutions, in essence, it is pretty useless, unless you already possess a degree from an accredited traditional educational institution. We will analyze the first two years of Harvard's attempt at offering open and free courses to all, we will look at its successes, failures and the way forward.</p> <p>The first two years 2012, 2013 Harvard offered only 5 courses. Out of the <strong>290,498</strong> registrations, <strong>49.2%</strong> of the students registered for Introduction to Computer Science, <strong>16.9%</strong> for Justice, <strong>13% </strong>for Health in numbers, <strong>12.2%</strong> for Human Health and Global environmental change and finally <strong>8.7%</strong> registered for the Ancient Greek Hero. When we break this down by gender, males outnumber females in overall registration by <strong>106,149</strong>. Analyzing individual course registration, males still outnumber females, we see this in all the courses listed and even more significantly in the Computer science subject.</p> <p>The goal of MOOCs is to make world class education accessible to all persons including students from developing countries. We do see however that the United States leads the pack in student enrollments (which is a developed country) instead of the targeted countries from the global south. <strong>78.8%</strong> of students who registered for the courseware were between ages <strong>16 and 34</strong>, we can be reasonably confident and say that most of the students are either millennials or generation z. <strong>68%</strong> of the students who registered for the courseware already possess either a bachelor's, master's or a doctorate degree(s).</p> <p>MOOCs have grown in number and popularity but failed to live up to its mission of democratizing education around the world. Out of the <strong>290948</strong> students who registered for the HarvardX open courseware in 2012 and 2013, only <strong>65,261</strong> completed the courseware representing <strong>22.4%</strong> of total student enrollments. Out of the <strong>65,261</strong> who completed the courseware only <strong>5728</strong> received certifications, distressingly representing <strong>2%</strong> of total student enrollments.</p> <p>Certification rate in general is disappointingly low but we want to see if this is true for all demographics in this dataset. We will analyze individual courses, student age, level of education as well as the country of origin to perhaps diagnose the problem of low completion and low certification. First, out of <strong>143,266</strong> students who registered for Introduction to Computer Science, only <strong>1%</strong> were certified. Out of <strong>49,293</strong> students who registered for Justice, <strong>4%</strong> were certified. Out of <strong>37709</strong> students who registered for Health in numbers, <strong>5%</strong> were certified. Out of the <strong>35509</strong> students who registered for Human health and global environmental change, <strong>2%</strong> were certified. Out of the <strong>25171</strong> students who registered for the Ancient Greek hero, only <strong>1%</strong> received certifications.</p> <p>Secondly, about 73% of the students who completed the courseware and received certification already have a bachelor's, master's or doctorate degree(s). This shows that students accessing the courseware regard it merely as a resource to fill in gaps to supplement skills already learnt in a four year traditional institution. Additionally about 67% of those who received certifications fall within ages 16 to 30 which is the targeted age group, the only problem is that there are simple not enough certifications for students within this age group compared to the number of enrollments. Out of the 229301 students enrollments who fall within this age group, only 3822 received certifications representing 1.67% of enrollments.</p> <p>We can agree that MOOCs began conceptually as a great idea but fails in implementation, the simple truth is that attitudes towards initiatives labelled 'free' in certain parts of the world encourage apathy. We see that in most countries from every continent except for Europe. Secondly, some students need external discipline to stay committed and complete the courseware but because the stakes are low and there is nothing to lose, most students simply do not see the reason to do so. Thirdly, a large number of those who registered for these courses as well as those who received certifications were from developed countries, failing to democratize education for those who need it the most, students from the global south.</p>
Student's logs and perceptions of an automated assessment tool in a software engineering MOOC specialization
<p>Our dataset contains students' perceptions and usage of an automated assessment tool (MOOCauto) for obtaining formative feedback in software engineering assignments that are part of a MOOC specialization at Universidad Politécnica de Madrid (Spain), delivered by the MiriadaX platform. The dataset has previously been used in a study to evaluate students' perceptions of the tool and to analyze their usage patterns using Growth Mixture Models <a href="https://www.computer.org/csdl/magazine/so/5555/01/10196480/1P9AhkBLYXK">(López-Pernas et al., 2023)</a>. The code of each of the assignments is available on Github: <a href="https://github.com/ging-moocs">https://github.com/ging-moocs</a>.</p> <p>Our dataset contains two files:</p> <h2>MOOCauto usage logs</h2> <p>The first file is called<strong> moocauto_logs.csv </strong>and it contains 9,108 anonymized logs of students' use of the automated assessment tool in the MOOC specialization assignments. The columns of the dataset are as follows:</p> <ul> <li><strong>MOOCid</strong>: Unique numeric identifier for the MOOC (1-4)</li> <li><strong>MOOC: </strong>Name of the MOOC: Frontend Development, Backend Development, Git & Github, Fullstack Development</li> <li><strong>AssignmentName</strong>: Name of the assignment.</li> <li><strong>AssignmentId</strong>: Unique identifier for each assignment (1-17)</li> <li><strong>user: </strong>Unique identifier of the student (it varies per assignment)</li> <li><strong>timestamp: </strong>Time in which the assessment was performed</li> <li><strong>score</strong>: Score obtained (0-10)</li> </ul> <h2>Students' perceptions of MOOCauto</h2> <p>The second file is called <strong>moocauto_questionnaire.csv</strong> and it contains 213 students' responses to the questionnaire conducted at the end of each MOOC in order to evaluate their opinion of the tool and perception on usefulness, ease of use, and other aspects related to the Technology Acceptance Model (TAM). The questions were as follows:</p> <ul> <li><strong>What is your general opinion of MOOCauto?</strong> (1 Horrible - 5 Excellent)</li> <li><strong>Indicate your level of agreement with the following statements </strong>(1 Strongly disagree - 5 Strongly agree) <ul> <li>MOOCauto has been easy to install</li> <li>MOOCauto has been easy to use</li> <li>The feedback provided by MOOCauto was easy to understand</li> <li>The feedback provided by MOOCauto was useful</li> <li>The feedback provided by MOOCauto helped me improve my assignments</li> <li>The documentation Of MOOCauto was useful</li> <li>MOOCauto has increased my motivation to work on the assignments</li> <li>I prefer the feedback from MOOCauto than from peer assessment</li> <li>I would like to have a bot like MOOCauto in other MOOCs</li> </ul> </li> <li><strong>How useful do you perceive the following features of MOOCauto?</strong> (1 Useless - 5 Very useful) <ul> <li>It works locally on my computer</li> <li>It allows to run the test suite as many times as I want</li> <li>It provides instantaneous feedback every time the test suite is executed</li> <li>It has documentation that explains its use and available options</li> </ul> </li> </ul>
facebook-activity in a Mooc Course
<p>agentxknowledge: Dataset which gathers the information about the interaction performed by learners to certain topics published in facebook as social activity of a Mooc course. It consists on three columns: learner, topic and times that learner participated.</p> <p>agentxagent: Dataset which gathers the information about the interaction performed among learners who participated in a Mooc course. It consists on three columns: learner, learner and times that the first learner answered to the second learner.</p>
IDE Action Log Dataset from a CS1 MOOC
<p>This is a a dataset containing Integrated Development Environment (IDE) logs from an introductory programming MOOC. The dataset contains information on when actions in the IDE were performed in relation to deadlines over the different parts of the course. One exceptional aspect of the dataset is that part of the logs have been gathered at the keystroke level, allowing for fine-grained insight into the learning process. In addition to the IDE logs themselves, the dataset has information on whether students included in the data passed the course. This can facilitate further research that analyzes how time-related behavior relates to performance in introductory programming courses.</p>
TU Delft Open Science MOOC survey 2018
<p>The dataset contains a survey resultas conducted by the Open Science MOCC in Assignment 1. The results include the researchers' opinions regarding the Open Science topics.</p>
DDJ MOOC courses
<p>Data Sets from EJC.</p>
Individual project on theme "Cervus L." (MOOC: CompTech in biology)
<p><strong><span>Данный кейс является результатом реализации индивидуального проекта </span></strong><em><span>Попова Игоря</span></em><strong><span> по теме "</span></strong><em><span>C</span></em><em><span>ervus</span></em><em><span> </span></em><span>L</span><span>.</span><strong><span>" в рамках онлайн курса "Компьютерные технологии в биологии" (автор – А.В. Ваганов) (https://stepik.org/course/60859/promo)</span></strong></p>
Dataset on an Evaluation of MCQs from MOOCs for Common Item Writing Flaws
<p>This dataset is comprised of data collected from questions in 18 MOOCs in the areas of medical health education, life sciences and computer science. 204 questions were evaluated by two evaluators using an evaluation protocol from the literature. Over 50% of the MCQs (112) were found to have one or more item writing flaw; 57 of the MCQs contained two or more flaws. A considerable proportion of the MCQs were found to violate item-writing guidelines, which confirms findings of previous research in this area that examined rates of flaws in MCQs in traditional formal educational contexts. The issue of flawed MCQs can be addressed by training faculty in how to conduct quality checks before before and after their deployment. The data consists of an Excel file with several workbooks </p>
Agape Open Science MOOC
<p>Under Agape we aim to disseminate open science between PhD students and early career researchers across Ireland and later internationally. We want to create an open science practising community where we can learn, exchange our opinions and experiences, and together change the future. In the way that science is undertaken, made freely available, and communicated in a FAIR and transparent way.</p> <p> </p>
Unified MOOCs Semantic Search Engine
<p>Full dataset of Unified MOOCs</p>
Data for the MOOC MBD Study
<p>co authors at Aga Khan University and other institutes across Pakistan</p>
Dataset of Empirical MOOC Research 2016 - 2017
<p>Dataset of Empirical MOOC Research 2016 - 2018 </p>
FUNCERT - Registration dynamics and course certification rates on a Massive Open Online Course (MOOC) platform
<p>The FUNCERT data set describes 1 million course registration events collected over a 2-year period from the MOOC platform FUN (France Université Numérique, fun-mooc.fr). Each registration event is associated with a timestamp and an indication of whether a completion certificate was ultimately awarded. It was used in the referenced manuscript to model the impact of multiple course registrations on certificate rates.</p> <p>The data set is provided as a single file (FUNCERT.csv) with the following fields.</p> <p><strong>Time (min)</strong> The time of the registration event reported in minutes elapsed since the beginning of data collection. The time stamp is reported as a relative time only, not an exact calendar date, to enhance anonymization.</p> <p><strong>User ID</strong> A unique ID number for each user of the platform during this period. The number has been generated specifically for this data set and does not correspond to user ID numbers used within the FUN platform.</p> <p><strong>Course ID</strong> Each of the 140 offered courses is assigned a unique and anonymous ID code. In some cases courses were offered multiple times within the data collection period. The same Course ID is used across multiple instances of the same course.</p> <p><strong>Certificate</strong> A boolean variable set to 1 if the registration event is associated with a course completion certificate. Of 140 offered courses, 91 awarded certificates during the study period.</p> <p><strong>Age</strong> User age in years at the time of registration. Field may be left blank if data was not provided.</p> <p><strong>Gender</strong> User gender as selected from the options m and f. Field may be left blank if data was not provided.</p>
Curso MOOC de PC - Módulo 02 - Decomposição - Vídeo Explicativo
<p>Esse material faz parte do "CURSO MOOC DE PENSAMENTO COMPUTACIONAL" desenvolvido por bolsistas PIBIC/PIBITI e alunos de TCC do Bacharelado em Ciência da Computação do Instituto Federal do Ceará - Campus Tianguá, vinculados ao projeto de extensão LUA ACADEMY sob a coordenação da professora Cynthia Pinheiro Santiago.</p>
Curso MOOC de PC - Módulo 01 - Introdução - Vídeo Explicativo
<p>Esse material faz parte do "CURSO MOOC DE PENSAMENTO COMPUTACIONAL" desenvolvido por bolsistas PIBIC/PIBITI e alunos de TCC do Bacharelado em Ciência da Computação do Instituto Federal do Ceará - Campus Tianguá, vinculados ao projeto de extensão LUA ACADEMY sob a coordenação da professora Cynthia Pinheiro Santiago.</p>
Curso MOOC de PC - Módulo 03 - Reconhecimento de Padrões - Vídeo Explicativo
<p>Esse material faz parte do "CURSO MOOC DE PENSAMENTO COMPUTACIONAL" desenvolvido por bolsistas PIBIC/PIBITI e alunos de TCC do Bacharelado em Ciência da Computação do Instituto Federal do Ceará - Campus Tianguá, vinculados ao projeto de extensão LUA ACADEMY sob a coordenação da professora Cynthia Pinheiro Santiago.</p>
Curso MOOC de PC - Módulo 04 - Abstração - Vídeo Explicativo
<p>Esse material faz parte do "CURSO MOOC DE PENSAMENTO COMPUTACIONAL" desenvolvido por bolsistas PIBIC/PIBITI e alunos de TCC do Bacharelado em Ciência da Computação do Instituto Federal do Ceará - Campus Tianguá, vinculados ao projeto de extensão LUA ACADEMY sob a coordenação da professora Cynthia Pinheiro Santiago.</p>
Curso MOOC de PC - Módulo 05 - Algoritmo - Vídeo Explicativo
<p>Esse material faz parte do "CURSO MOOC DE PENSAMENTO COMPUTACIONAL" desenvolvido por bolsistas PIBIC/PIBITI e alunos de TCC do Bacharelado em Ciência da Computação do Instituto Federal do Ceará - Campus Tianguá, vinculados ao projeto de extensão LUA ACADEMY sob a coordenação da professora Cynthia Pinheiro Santiago.</p>
Materiales para el análisis y evaluación de Recursos Educativos Abiertos (REA) en MOOCs
<p>En este data sets se encuentran los documentos de la investigación "Impacto de la Inteligencia Artificial Generativa en la eficiencia, calidad e innovación en la producción de Recursos Educativos Abiertos para MOOC", publicados en la Revista Comunicación y Sociedad. Se adjuntan: 1) Operacionalización de variables y 2) Resultados de análisis</p> <p>Todos los Recursos Educativos en Abierto (REA) de los proyectos pueden consultarse en:</p> <p>Crescent: https://crescent.ciberimaginario.es/oer/ </p> <p>Dominoes: https://ciberimaginario.es/project/dominoes/</p> <p><strong>Financiaciación de la investigación:</strong></p> <p>Desarrollado en el marco de los proyectos Erasmus+ co-financiados por la Unión Europea: “Mind the gap in media CoveRagE and Strategic communication in CasE of security Threats” (CRESCent 2018-1-RO01-KA202-049449) y “Digital cOMpetences INformatiOn EcoSystem” (DOMINOES-2021-1-RO01-KA220-HED-000031163). La investigación cuenta con los siguientes apoyos: la Universidad Rey Juan Carlos (ID 501100007511) en el marco de la Convocatoria de Ayudas para Personal en Formación 2020 (PREDOC 20-008); la Comunidad de Madrid en el marco de la Ayuda para doctorados industriales (IND 2022/SOC-23503) con el convenio de colaboración con Prodigioso Volcán S.L; y la Convocatoria para la contratación de Ayudantes de investigación de la Comunidad de Madrid 2021 (PEJ-2021-AI/SOC-22035), Ref. Interna F844- 3981</p> <p> El apoyo de la Comisión Europea a esta publicación no constituye una aprobación de su contenido, que refleja únicamente las opiniones de los autores, y la Comisión no se hace responsable del uso que pueda hacerse de la información aquí difundida.</p>
Dataset MOOC Forum edX
<p>This dataset contains the information from the forum of three MOOCs on programming (multiple editions) offered through the edX platform. These MOOCs are offered in the Spanish and English versions.</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.