Online Social Presence: A Study of Score Validity of the Computer-Mediated Communication Questionnaire

The purpose of this study was to conduct a confirmatory factor analysis of the Computer-Mediated Communication Questionnaire scores, using structural equation modeling, to assess the consistency between the empirical data and the hypothesized factor structure of the CMCQ in the proposed models, which is stipulated by the theoretical framework and previous research. Online social presence is a vital affective learning factor that influences online interaction. In this study, online social presence was defined as the degree of feeling, perception, reaction, and trustworthiness of being connected by computer-mediated communication to another intellectual entity through electronic media. Currently, valid instruments to determine the degree of social presence felt and exhibited by online learners are wanting. The results of this study indicated that online social presence was multidimensional, and composed of 4 factors as hypothesized in the theoretical framework: social context, online communication, interactivity, and privacy, although revision of some test items was also suggested by the results

A Predictor for PLE Management: Impacts of Self-Regulated Online Learning on Student\u27s Learning Skills

Web 2.0 integration requires a high level of learner-centered skills to create a personal learning environment (PLE). The pedagogical capability of Web 2.0 could support and promote self-regulated learning (SRL) by enabling the constructions of PLEs. This study investigated how will each of the six aspects of self-regulated online learning (i.e., environment structuring, goal setting, time management, task strategies, help seeking, & self-evaluation) respectively predict the level of initiative, the sense of control, and the level of self-reflection in personal learning environment (PLE) management. The study concluded that all six aspects of SRL could predict three types of PLE management besides environmental structuring to the level of initiative. Educators need to prepare all learners to advance their SRL to achieve sufficient PLE skills and knowledge to become competent digital network learners

A Predictor for PLE Management: Impacts of Self- Regulated Online Learning on Students’ Learning Skills

Web 2.0 integration requires a high level of learner-centered skills to create a personal learning environment (PLE). The pedagogical capability of Web 2.0 could support and promote self-regulated learning (SRL) by enabling the constructions of PLEs. This study investigated how will each of the six aspects of self-regulated online learning (i.e., environment structuring, goal setting, time management, task strategies, help seeking, & self-evaluation) respectively predict the level of initiative, the sense of control, and the level of self-reflection in personal learning environment (PLE) management. The study concluded that all six aspects of SRL could predict three types of PLE management besides environmental structuring to the level of initiative. Educators need to prepare all learners to advance their SRL to achieve sufficient PLE skills and knowledge to become competent digital network learners

Assessment and Learning in Knowledge Spaces (ALEKS) Adaptive System Impact on Students\u27 Perception and Self-Regulated Learning Skills

Adaptive learning is an educational method that uses computer algorithms and artificial intelligence (AI) to customize learning materials and activities based on each user\u27s model. Adaptive learning has been used for more than 20 years. However, it is still unique, and no other system could bring more or even similar capabilities than the ones adaptive technology offers, including the application of AI, psychology, psychometrics, machine learning, and providing a personalized learning environment. However, there are not many studies on its practicality, usefulness, improving students\u27 learning skills, students\u27 perception, etc., due to the limited number of institutes investing in this new technology. This paper presents the results of administering the newly developed Adaptive Self-regulated Learning Questionnaire (ASRQ) in an adaptive learning course equipped with the ALEKS (Assessment and Learning in Knowledge Spaces) system to study the amount of Self-regulated Learning Skills (SRL) score change, if any, of the students. The ASRQ was administered at the beginning and end of the semester as a pretest and posttest. Then, the quantitative Sample Paired t Test was run to measure the students\u27 SRL score change between the beginning and end of the semester. The results showed a significant decline in students\u27 SRL skills score while working with ALEKS. This paper also discusses the reasons for the considerable drop in SRL skills based on students\u27 perception and feedback collected through administering an open-ended survey at the end of the semester. The survey\u27s qualitative analysis showed various possible factors contributing to the decline of the SRL skills score, including lack of motivation, system complexity, hard penalty, lack of social presence, and lack of system practicality

Using Personal Learning Environment (PLE) Management to Support Digital Lifelong Learning

Personal Learning Environment is a promising pedagogical approach to integrate formal and informal learning in social media and support student self-regulated learning. The use of PLEs to support lifelong learning can be expanded to the formal, non-formal, or informal learning environments. This study empirically examined how PLE management predicted the use of PLE to support three types of lifelong learning (i.e., formal, non-formal, or informal learning). This study concluded that PLE management was predictive of each type of learning respectively. PLE is not only a technical platform but also a new digital learning literacy, conceptual space, pedagogical process, and social networks that enable and support learners to achieve their lifelong learning goals. While Open Educational Resources (OERs) are perceived as a solution for social justice in digital lifelong learning, PLE and Open Network Learning Environment are identified as the key pedagogy and instructional strategies to empower learners gaining network-learning literacy and becoming competent digital lifelong learners

Online Adaptive Learning: A Study of Score Validity of the Adaptive Self-Regulated Learning Model

Adaptive Learning (AL), a new web-based online learning environment, requires self-regulated learners who act autonomously. However, to date, there appears to be no existing model to conceptualize different aspects of SRL skills in Adaptive Learning Environments (ALE). The purpose of this study was to design and empirically evaluate a theoretical model of Self-Regulated Learning (SRL) in ALE\u27s and the related questionnaire as a measurement tool. The proposed theoretical model, namely, “Adaptive Self-Regulated Learning (ASR)”, was specified to incorporate the SRL skills into ALE\u27s. Based on this model, the Adaptive Self-regulated Learning Questionnaire (ASRQ) was developed. The reliability and validity of the ASRQ were evaluated via the review of a content expert panel, the Cronbach\u27s alpha coefficients, and confirmatory factor analysis. Overall, the results supported the theoretical framework and the new ASRQ in an ALE. In this article, the theoretical and practical implications of the findings were discussed

Application and comparison of scoring indices to predict outcomes in patients with healthcare-associated pneumonia

Introduction: Healthcare-associated pneumonia HCAP is a relatively new category of pneumonia. It refers to infections that occur prior to hospital admission in patients with specific risk factors following contact or exposure to a healthcare environment. There is currently no scoring index to predict the outcomes of HCAP patients. We applied and compared different community acquired pneumonia CAP scoring indices to predict 30-day mortality and 3-day and 14-day intensive care unit ICU admission in patients with HCAP. Methods: We conducted a retrospective cohort study based on an inpatient database from six medical centers, recruiting a total of 444 patients with HCAP between 1 January 2007 and 31 December 2007. Pneumonia severity scoring indices including PSI pneumonia severity index, CURB 65 confusion, urea, respiratory rate, blood pressure , age 65, IDSA/ATS Infectious Diseases Society of America/American Thoracic Society, modified ATS rule, SCAP severe community acquired pneumonia, SMART-COP systolic blood pressure, multilobar involvement, albumin, respiratory rate, tachycardia, confusion, oxygenation, pH, SMRT- CO systolic blood pressure, multilobar involvement, respiratory rate, tachycardia, confusion, oxygenation, and SOAR systolic blood pressure, oxygenation, age, respiratory rate were calculated for each patient. Patient characteristics, co-morbidities, pneumonia pathogen culture results, length of hospital stay LOS, and length of ICU stay were also recorded. Results: PSI > 90 has the highest sensitivity in predicting mortality, followed by CURB-65 >= 2 and SCAP > 9 SCAP score area under the curve AUC: 0.71, PSI AUC: 0.70 and CURB-65 AUC: 0.66. Compared to PSI, modified ATS, IDSA/ATS, SCAP, and SMART-COP were easy to calculate. For predicting ICU admission Day 3 and Day 14, modified ATS AUC: 0.84, 0.82 , SMART-COP AUC: 0.84, 0.82, SCAP AUC: 0.82, 0.80 and IDSA/ ATS AUC: 0.80, 0 .79 performed better statistically significant difference than PSI, CURB- 65, SOAR and SMRT-CO. Conclusions: The utility of the scoring indices for risk assessment in patients with healthcare-associated pneumonia shows that the scoring indices originally designed for CAP can be applied to HCAP

Online Accelerated Learning Experiences and Self-Regulated Learning Skills Amoung Undergraduate Students

Many institutions have adopted an online accelerated learning model in which intensive online instructions are offered during the course of a normal semester to help students complete classes. Current research has focused on comparing different instructional lengths. Mixed findings have been reported. Accelerated instructions are not necessarily superior or inferior to traditional 16-week instructions. Research should focus on what is crucial and how to prepare students to succeed in accelerated online courses. This study examines whether self-regulated learning (SRL) skills may serve as predictors of positive accelerated learning experiences. It concludes that five SRL skills can predict success in online accelerated learning experiences and suggested educators should identify and prepare students with relevant SRL skills prior to attempting accelerated instructions to warrant a positive learning experience

A Predictive Study of Students’ Self-regulated Learning Skills and Their Roles in the Social Network Interaction of Online Discussion Board

Online learners’ learning skills and behaviors are challenging for educators to foresee, particularly what skills may be related to certain social interaction behaviors. Self-regulated learning (SRL) skills are critical to online learning. It is unclear how SRL skills may predict social network interaction. This study empirically investigated: How will SRL skills predict students’ network roles (i.e., in-degree, out-degree, betweenness centrality, closeness centrality, eigenvector centrality, reciprocated vertex pair ratio, & PageRank) in the social network discussions of discussion board within online courses? The predictive utility of SRL skills for betweenness and closeness centralities was supported. Learners with greater SRL skills play more influential roles in online discussion network. Learners with higher SRL skills tend to connect to others based on flow and distance of the connections, rather than how prominent (eigenvector) and prestigious (PageRank) of their connections