دانلود رایگان مقاله لاتین الگو دانش آموزان از عملکرد دوره از سایت الزویر
عنوان فارسی مقاله:
الگوهای دانش آموزان از عملکرد دوره و تعامل در یک دوره آزاد انبوه آنلاین
عنوان انگلیسی مقاله:
Students’ patterns of engagement and course performance in a Massive Open Online Course
سال انتشار : 2016
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مقدمه انگلیسی مقاله:
1. Introduction
Massive Open Online Courses are a unique form of online education due to an absence of admission criteria, a highly diverse student population and a variety of motives for taking the course. The term “Massive Open Online Course” (MOOC) was first used to describe a twelve-week online course, Connectivism and Connected Knowledge, designed by George Siemens and Stephen Downes, offered at the University of Manitoba, Canada, in fall semester 2008 (Cormier & Siemens, 2010). “Massive” regards the capacity for courses to enroll large numbers of students, as well as to track vast quantities of participant activity and performance data. “Open” refers to low to free cost to participate as learners see fit, and materials for the course that are accessible to all users with an adequate Internet connection. As online courses, MOOCs are available via the Internet on a variety of devices and thus expand access beyond the traditional campus. Labeled a “course,” a MOOC is framed in a time period with a beginning and an end point; provides a coherent set of resources; and follows a sequence of activities organized by an instructor in order to address specific learning objectives. Current research on MOOCs highlights issues such as the influence of MOOCs on the future of higher education (Billington & Fronmuller, 2013), the effects of MOOCs on teachingand learning (Martin, 2012), what educational problems MOOCs might solve (Rivard, 2013), gaps in MOOC research (Liyanagunawardena, Adams, & Williams, 2013), and blending face-to-face classes with online MOOC classes (Bruff, Fisher, McEwen, & Smith, 2013). Classifications of MOOCs may vary depending upon the pedagogical interactions, learning outcomes or the participant's experience (Haavind & Sistek-Chandler, 2015). Common in the literature are the two kinds of MOOCs: xMOOCs and cMOOCs. This classification is based on the course content structure, expectations of students' performance and assessment methods. The vast majority of existing MOOCs are content-based MOOCs, known as xMOOCs, which present the course content through different knowledge packages and methods that assess learners' mastery of the knowledge (Kim, 2015). Course content usually includes short lecture videos each week, often supported by supplementary readings, and assignments. Assessments that count towards the participant's final score are provided, usually weekly, in the form of multiple-choice or short answer quizzes that are auto-graded, and peer-graded assignments. Online discussion forums are also included to allow participants to engage with each other and exchange knowledge and ideas, or to create a sense of community (Hollands & Tirthali, 2014). Connectivist MOOCs, known as cMOOCs, are more fluid in structure. They focus more on an overarching instructional goal and are less directive with respect to process. Learners in a cMOOC build their knowledge through co-creation assignments with peers. Instructors may pose initial or weekly questions and challenges together with a variety of text-based or media resources. Learners interact and cooperate with one another in carrying out the co-creation task. The success of a cMOOC is highly dependent on participant interaction via discussion forums. However, the challenges to make this interaction happen lie at the different starting point of the prior knowledge of the learners (Andersen & Ponti, 2014). Course outcomes are often unique products, such as blog posts, images, diagrams, or videos generated by participants using a variety of social media. The role of the instructor is to act as a facilitator by aggregating, reviewing, summarizing and reflecting on participant activity on a daily or weekly basis (Hollands & Tirthali, 2014). Thus, the boundaries between the MOOC types are not clear. There are some MOOCs that fit in between an xMOOC and a cMOOC. This third type of MOOC is called pMOOC (or project-based MOOC), which is a content-based, highly structured MOOC in terms of how the course content is organized and presented, but also blends a project-based model of assessment. In this type of MOOC, the task for the student is to design a project that is reviewed by peers using an articulated rubric, created by the instructor or teaching staff (Haavind & Sistek-Chandler, 2015). Course completion requirements in a pMOOC typically include submitting projects for peer grades and reviews of a number of mini-projects designed by peers (Haavind & Sistek-Chandler, 2015). The DS MOOC, the subject of this study, fits the description of a pMOOC. It is a five-week MOOC equivalent to five phases of producing a digital story. For each week, instructional materials including video lectures, readings, and examples of digital stories to watch are presented together with the week's assignment for the student to perform. The week's assignment can be seen as a mini project that builds on one another towards the final project, a complete digital story at the end. Students’ submitted assignments at most phases of the course are assigned to be graded by peers using articulated rubrics created by the instructor. Students are also exemplified with sample grading for each assignment using the rubric. This paper investigates possible factors for learners' success in the above mentioned DS MOOC, the pMOOC offered in September 2014. It examines potential relationships between students' course performance and their patterns and degree of involvement, their motives of participation as well as their subject matter knowledge prior joining the MOOC. Data on the students' course performance were retrieved from the data pool collected by Coursera and provided to the instructors. . Data on the students’ patterns, degree and motives of participation as well as their subject knowledge of digital storytelling prior participating in the MOOC were collected through a post-course survey. Results of the study will allow the development team to reinforce and strengthen factors related to motivation and engagement in the design of the next MOOCs.
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کلمات کلیدی:
Visualizing patterns of student engagement and performance in MOOCs dl.acm.org/citation.cfm?id=2567586 by C Coffrin - 2014 - Cited by 73 - Related articles Mar 24, 2014 - In the last five years, the world has seen a remarkable level of interest in Massive Open Online Courses, or MOOCs. A consistent message from ... Student Engagement Patterns over the Duration of Level 1 and Level ... www.tandfonline.com/doi/abs/10.1080/03098265.2010.498880 by M Stewart - 2011 - Cited by 29 - Related articles Dec 1, 2010 - Student Engagement Patterns over the Duration of Level 1 and ... on Student Attendance, Performance and Use of Online Resources ... This study explores patterns of student engagement across two geography courses. [PDF]Learning Latent Engagement Patterns of Students in Online Courses https://www.cs.purdue.edu/homes/dgoldwas/papers/RGHDGAAAI14.pdf by A Ramesh - 2014 - Cited by 37 - Related articles Learning Latent Engagement Patterns of Students in Online Courses. 1Arti Ramesh .... academic performance for traditional classroom courses; they identify ... [PDF]Engagement Patterns of High and Low ... - Libertas Academica insights.sagepub.com/redirect_file.php?fileId...Engagement-Patterns-of... by AA Jaffar - 2016 - Cited by 1 - Related articles Feb 4, 2014 - CITATION: Jaffar and eladl. engagement patterns of High and low academic performers ... Students in higher education courses,8 including medical students,9,10 ... academic performance exists only in students who are more. Visualizing patterns of student engagement and performance in MOOCs. www.academia.edu/.../Visualizing_patterns_of_student_engagement_and_performanc... Visualizing patterns of student engagement and performance in MOOCs. .... This to develop a greater understanding of students' patterns of linear course design ... The utilization of data analysis techniques in predicting student ... https://telrp.springeropen.com/articles/10.1186/s41039-015-0007-z by G Hughes - 2015 - Cited by 10 - Related articles Jul 16, 2015 - However, analysis of engagement with course material, via learning management ... be used to analyze student-generated data in order to find patterns of system usage ... Student engagement and performance in MOOCs.
