scholarly journals FROM POSTS TO PATTERNS: A METRIC TO CHARACTERIZE DISCUSSION BOARD ACTIVITY IN ONLINE COURSES

2019 ◽  
Vol 13 (2) ◽  
Author(s):  
Catherine A. Bliss ◽  
Betty Lawrence
Keyword(s):  
Online Courses ◽  
Large Data ◽  
Discussion Board ◽  
Discussion Boards ◽  
Participation Rates ◽  
Data Set ◽  
Mathematics Courses ◽  
State College ◽  
Empire State College

Asynchronous text based discussion boards are included in many online courses, however strategies to compare their use within and between courses, from a disciplinary standpoint, have not been well documented in the literature. The goal of this project was to develop a multi-factor metric which could be used to characterize discussion board use in a large data set (n=11,596 message posts) and to apply this metric to all Mathematics courses offered in the January 2008 term by the Center for Distance Learning at Empire State College. The results of this work reveal that student participation rates, quantity of student posts, quality of student posts and the extent of threading are well correlated with instructor activity.

scholarly journals Measuring Faculty-Student Interaction in Online Courses Using Asynchronous Discussion Boards

2020 ◽  
Author(s):  
Crystal Gasell
Keyword(s):  
Student Satisfaction ◽  
Social Exchange ◽  
Learning Analytics ◽  
Online Courses ◽  
Discussion Board ◽  
Management Systems ◽  
Discussion Boards ◽  
Instructor Interaction ◽  
Data Points ◽  
Learning Management

Online learning is growing. As such, institutions want to grow programs, while ensuring quality. Part of ensuring quality in online courses is ensuring that there is regular and substantive interaction (RSI) between students and instructors. Discussion boards are often used in online courses as a way to promote social exchange, interaction, and the discussion of course concepts. Therefore, discussion board activity can provide a glimpse into the RSI that occur between students and instructors. Until recently, data from learning management systems was difficult to access and analyze. However, advances in technology and an increased interest in learning analytics provides researchers and institutions with billions of data points about student and instructor activity within a learning management system (LMS). This study used LMS data to explore the frequency of interaction between instructors and students in discussion boards in online courses at one institution. 415 courses were selected for the study, spanning two semesters. Results from the study found that the average number of posts by an instructor was 32.9. The average instructor interaction was 1.49 instructor posts per student. 23% of courses had no instructor posts. Student posts averaged 470 per course and the average posts per student was 19.9. Based on the discussion board activity, the most discussion interaction occurred during the first two weeks of the semester. Results suggested that there is no relationship between student satisfaction and the number of total posts in a course.

scholarly journals A good sine? Seeking math help using crowdsourced online discussion boards

2019 ◽  
Vol 17 (1) ◽  
pp. 78-93
Author(s):  
Ann Y Kim ◽  
Ian Thacker
Keyword(s):  
Learning Strategies ◽  
Online Discussion ◽  
Discussion Board ◽  
Discussion Boards ◽  
Self Regulated Learning ◽  
Online Discussion Board ◽  
Asynchronous Online Discussion ◽  
One Year ◽  
Khan Academy

We examined asynchronous online discussion boards, specifically those that are unmediated by teacher figures, to identify characteristics of these spaces that support or constrain students as they seek help in mathematics. We analyzed 86 questions and 114 associated responses posted to two Khan Academy discussion boards centered around two related trigonometry lessons. The platform created a space where students could ask a variety of questions ranging from those requesting math definitions and explanations of math procedures to justifications for why formulas are true. However, crowdsourced replies to questions were delayed, sometimes taking more than one year for a reply to be posted; content of student replies did not always match the content of the questions posed; and the quality of the replies varied considerably, some replies were helpful or resourceful while others were incorrect or vague. These challenges seemed connected to the unmediated nature of this type of asynchronous online discussion board. We argue that this online learning environment demands additional self-regulated learning strategies such as awareness of one’s needs and the timeframe in which they must be met. We also discuss implications for research and practice.

scholarly journals To Optimize Network Call Drops and Enhances Real Time (CDR) Data Handling with Security

2020 ◽  
Author(s):  
Ashok G V ◽  
Dr.Vasanthi Kumari P
Keyword(s):  
Real Time ◽  
Service Providers ◽  
Large Data ◽  
Network Capacity ◽  
Data Set ◽  
Satisfaction Index ◽  
Customer Churn ◽  
Trend Forecasting ◽  
Telecom Networks

The telecom networks generate multitudes and large sets of data related to networks, applications, users, network operations and real time call processing (Call Detail Record (CDR)). This large data set has the capability to give valuable business insights - for example, real-time user quality of service, network issues, call drop issues, customer satisfaction index, customer churn, network capacity forecast and many more revenue impacting insights. As even setting up of more towers for better coverage would also directly affect the health of habitants around. In this paper, the overall condition of call drops has been reviewed and possible ways to minimize the spectacles of network call drops. Applied Linear Regression algorithm which is used type of predictive analysis. Three major uses for regression analysis Determining the strength of predictors, Forecasting an effect and Trend forecasting. This paper gives to telecom service providers to improve their networks and minimize the network call drops with security. Deliver quality of services to their subscribers using the advanced technologies with accurate algorithms.

Best Practices for Engaging Graduate Students in Problem-Based Learning

2019 ◽  
pp. 21-48
Author(s):  
Marcella Jeanne Kehus
Keyword(s):  
Graduate Students ◽  
Best Practices ◽  
Online Courses ◽  
Online Discussion ◽  
Problem Based Learning ◽  
Discussion Board ◽  
Discourse Community ◽  
Discussion Boards ◽  
Online Discussion Board ◽  
The One

In this chapter, the author discusses two graduate online courses and the use of the online discussion boards specifically as they were used for problem-based learning. In the first course, the instructor scaffolded the learning more closely by providing a specific case to be solved by students and by providing specific instructions. In the second course, students were in the field tutoring and were to use the online discussion board as a place to bring their problems or issues to be problem-solved by the group. In this second context, graduate students became a discourse community developed their own ways of solving problems, working sometimes as more knowledgeable others and sometimes as the one seeking assistance, and generally encouraged each other. The instructor, after providing instruction and modeling during the first course, had little role during the second course besides providing resources, monitoring, and providing occasional corrections.

Comparison of Non-Destructive Examination Techniques for Crack Inspection

2020 ◽  
Author(s):  
Axel Aulin ◽  
Khurram Shahzad ◽  
Robert MacKenzie ◽  
Steven Bott
Keyword(s):  
Internal Surface ◽  
Large Data ◽  
Field Measurements ◽  
Management Program ◽  
Destructive Testing ◽  
Data Set ◽  
Examination Techniques ◽  
Welded Pipe ◽  
Non Destructive

Abstract Effective and efficient crack management programs for liquids pipelines require consistent, high quality non-destructive examination (NDE) to allow validation of crack in-line inspection (ILI) results. Enbridge leveraged multiple NDE techniques on a 26-inch flash-welded pipe as part of a crack management program. This line is challenging to inspect given the presence of irregular geometry of the weld. In addition, the majority of the flaws are located on the internal surface, so buffing to obtain accurate measurements in the ditch is not possible. As such, to ensure a robust validation of crack ILI performance on the line, phased array ultrasonic testing (PAUT), time-of-flight diffraction (TOFD), and a full matrix capture (FMC) technology were all used as part of the validation dig program. PAUT and FMC were used on most of the flaws characterized as part of the dig program providing a relatively large data set for further analysis. Encoded scans on the flash welded long seam weld were collected in the ditch and additional analyses were performed off-site to characterize and size the flaws. Buff-sizing where possible and coupon cutouts were selected and completed to assist with providing an additional source of truth. Secondary review of results by an NDE specialist improved the quality of the results and identified locations for rescanning due to data quality concerns. Physical defect examinations completed after destructive testing of sample coupon cutouts were utilized to generate a correlation between the actual defect size from fracture surface observation and the field measurements using various NDE methods. This paper will review the findings from the program, including quality-related learnings implemented into standard NDE procedures as well as comparisons of detection and sizing from each methodology. Finally, a summary of the benefits and limitations of each technique based on the experience from a challenging inspection program will be summarized.

Online Course Delivery: Issues of Faculty Development

1996 ◽  
Vol 25 (2) ◽  
pp. 127-131 ◽  
Author(s):  
Betty Hurley Lawrence
Keyword(s):  
Faculty Development ◽  
Online Courses ◽  
Computer Conferencing ◽  
Course Delivery ◽  
Online Course ◽  
Education Programs ◽  
Online Delivery ◽  
State College ◽  
Empire State College ◽  
New Material

An exciting option for distance education programs is to incorporate the use of computer conferencing. Yet, the adoption of this format has implications for course delivery. Two essential factors need to be taken into consideration: the increased flexibility provided by the format and the opportunity for student-student interaction. Increased flexibility comes from the ability to introduce new material through the conference that complements the contents of the accompanying text and course guide. Opportunity for increased interaction brings the challenge to make this interaction effective and beneficial. As more faculty move to use online delivery, they need assistance so they can make the most of the advantages of this environment. The Center for Distance Learning of SUNY Empire State College has been offering online courses for a number of years and has recently been developing workshops and materials to facilitate faculty development in this area.

scholarly journals Empire State College: The Development of Online Learning

2001 ◽  
Vol 1 (2) ◽  
Author(s):  
Patricia J. Lefor ◽  
Meg Benke ◽  
Evelyn Ting
Keyword(s):  
New York ◽  
Online Courses ◽  
Cost Effective ◽  
Professional Staff ◽  
Nontraditional Student ◽  
Full Time ◽  
Quality Cost ◽  
Online Programs ◽  
State College ◽  
Empire State College

Empire State College was founded in 1971 to meet the needs of adult and other nontraditional student populations in the state of New York. Its initial delivery model was individualized instruction with a student working with a full-time faculty member to develop a unique plan of study and learning contracts to support that plan. By 1979, the College established the Center for Distance Learning, which developed and still offers structured, print-based courses to students with no requirement for on-site meetings. It began to experiment with computer-supported learning activities in the late 1980s, employing professional staff to support the exploration of technology and to provide assistance to faculty in instructional design. However, it was not until 1994, with the formal creation of the Center for Learning and Technology, that the development of online courses and programs was systematically pursued. This article outlines the development of online programs since that time, emphasizing the issues and challenges faced by the institution in seeking to provide quality, cost-effective distance education.

Constrained Data Mining

2011 ◽  
pp. 301-306
Author(s):  
Brad Morantz
Keyword(s):  
Data Mining ◽  
Processing Time ◽  
Large Data ◽  
Computational Time ◽  
Data Sets ◽  
Data Set ◽  
Second Stage ◽  
Output Constraints ◽  
Ordered Data

Mining a large data set can be time consuming, and without constraints, the process could generate sets or rules that are invalid or redundant. Some methods, for example clustering, are effective, but can be extremely time consuming for large data sets. As the set grows in size, the processing time grows exponentially. In other situations, without guidance via constraints, the data mining process might find morsels that have no relevance to the topic or are trivial and hence worthless. The knowledge extracted must be comprehensible to experts in the field. (Pazzani, 1997) With time-ordered data, finding things that are in reverse chronological order might produce an impossible rule. Certain actions always precede others. Some things happen together while others are mutually exclusive. Sometimes there are maximum or minimum values that can not be violated. Must the observation fit all of the requirements or just most. And how many is “most?” Constraints attenuate the amount of output (Hipp & Guntzer, 2002). By doing a first-stage constrained mining, that is, going through the data and finding records that fulfill certain requirements before the next processing stage, time can be saved and the quality of the results improved. The second stage also might contain constraints to further refine the output. Constraints help to focus the search or mining process and attenuate the computational time. This has been empirically proven to improve cluster purity. (Wagstaff & Cardie, 2000)(Hipp & Guntzer, 2002) The theory behind these results is that the constraints help guide the clustering, showing where to connect, and which ones to avoid. The application of user-provided knowledge, in the form of constraints, reduces the hypothesis space and can reduce the processing time and improve the learning quality.

scholarly journals Participation in Online Courses and Interaction With a Virtual Agent

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Donggil Song ◽  
Marilyn Rice ◽  
Eun Young Oh
Keyword(s):  
Online Learning ◽  
Online Courses ◽  
Discussion Board ◽  
Virtual Agent ◽  
Learner Participation ◽  
Learner Achievement ◽  
Interaction Factor ◽  
Two Factors ◽  
Discussion Postings

Online learning environments could be well understood as a multifaceted phenomenon affected by different aspects of learner participation including synchronous/asynchronous interactions. The aim of this study was to investigate learners’ participation in online courses, synchronous interaction with a conversational virtual agent, their relationships with learner performance, and the participation/interaction factor identification. To examine learner participation, we collected learning management system (LMS) log data that included the frequency and length of course access, discussion board postings, and final grades. To examine synchronous learner interaction, we collected learners’ conversation logs from the conversational agent. We calculated the quantity and quality of discussion postings and conversations with the agent. The results showed that the frequency and length of course access, the quantity and quality of discussion postings, and the quality of conversation with the agent were significantly associated with the learner achievement. This study also identified two factors that comprise online learning participation and interaction: interaction quality and LMS-oriented interaction.

Emerging Big Data Sources for Community of Inquiry-Focused Educational Researchers

2018 ◽  
pp. 15-33
Keyword(s):  
Social Media ◽  
Big Data ◽  
Social Presence ◽  
Community Of Inquiry ◽  
Online Courses ◽  
Large Data ◽  
Discussion Board ◽  
Traditional Learning ◽  
Data Sets ◽  
Community Of Inquiry Framework

This chapter extends on concepts from Chapter 1, namely the Community of Inquiry framework, and provides a further glimpse into the overarching trends in the more recent literature. Trends in the recent CoI literature include a focus beyond discussion board data, movement into social media, and a focus on big data. The relevance of social presence is explored as a crucial component of the CoI framework. The authors extend the idea of learning in community beyond the traditional learning management system into digital spaces such as social media (e.g., Twitter) that lends itself to analyses of large data sets. This chapter also provides concrete research vignettes into how one researcher has journeyed from single course research using the CoI framework to conceptualizing and designing study across multiple online courses and years of data collection. Such an evolution or transformation from small data research to big data is detailed.

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