scholarly journals Learning analytics dashboard for twitter

2021 ◽  
Author(s):  
Anatoliy Gruzd ◽  
Nadia Conroy
Keyword(s):  
Learning Analytics ◽  
Online Survey ◽  
Qualitative Assessment ◽  
Named Entities ◽  
System Data ◽  
Twitter Users ◽  
The Individual ◽  
Intuitive Interface ◽  
Analytical Tools ◽  
Future Work

Designing a Learning Analytics Dashboard for Twitter-Facilitated Teaching Considering the increasing use of Twitter for both formal and informal learning, the primary goal of this project is to design a Learning Analytics (LA) dashboard to support instructors’ evaluation of Twitter-based teaching. To achieve this goal, we conducted an online survey involving 54 higher education instructors who have used Twitter in their past teaching. The main purpose was to identify why instructors use Twitter and what types of analytics they would consider valuable. The results of the survey evidence that instructors use Twitter to help students engage with class material, promote discussion, and build learning communities. Instructors expressed interest in analytical tools to help them quantitatively and qualitatively interpret Twitter data. Coupled with an in-depth literature review in this area, we relied on the survey data to prototype a Learning Analytics dashboard (https://dashboard.socialmediadata.org/educhat). Our online dashboard uses a simple, easy-to-read interface in accordance with previous successful dashboard implementations. Graphical visualizations allow instructors to monitor discussion patterns, such as the frequency and times of posting. Visual content breakdowns by number of retweets, original posts, and topics in the form of hashtags and named entities reveal the constituents of students’ posts. The dashboard provides additional analysis in the form of sentiment and subjectivity ranking as a way to contextually aid qualitative assessment. To support instructors’ awareness of class participation, we incorporated two visualizations that highlight the most active users and individuals who are most frequently mentioned in others’ tweets. Instructors can use the dashboard to gauge the participation at the individual- or classroom-level, and further discover what topics and links students discuss and share on Twitter. Three instructors piloted the LA dashboard over a 4-month semester in the Fall of 2017. Following their use, we conducted evaluation interviews with these instructors. Instructor evaluations confirmed that the proposed design is aligned with their pedagogical needs; they favored an intuitive interface that combined summative metrics for the entire class and personalized assessment of individual students. Based on instructors’ feedback, our future work will iteratively refine the design by integrating additional interactive features to adjust time scales of the output, investigate source data, collect data from lists of Twitter users (as opposed to a single hashtag), and further integrate the dashboard with other LMS (Learning Management System) data.

scholarly journals Learning analytics dashboard for twitter

2021 ◽  
Author(s):  
Anatoliy Gruzd ◽  
Nadia Conroy
Keyword(s):  
Learning Analytics ◽  
Online Survey ◽  
Qualitative Assessment ◽  
Named Entities ◽  
System Data ◽  
Twitter Users ◽  
The Individual ◽  
Intuitive Interface ◽  
Analytical Tools ◽  
Future Work

Designing a Learning Analytics Dashboard for Twitter-Facilitated Teaching Considering the increasing use of Twitter for both formal and informal learning, the primary goal of this project is to design a Learning Analytics (LA) dashboard to support instructors’ evaluation of Twitter-based teaching. To achieve this goal, we conducted an online survey involving 54 higher education instructors who have used Twitter in their past teaching. The main purpose was to identify why instructors use Twitter and what types of analytics they would consider valuable. The results of the survey evidence that instructors use Twitter to help students engage with class material, promote discussion, and build learning communities. Instructors expressed interest in analytical tools to help them quantitatively and qualitatively interpret Twitter data. Coupled with an in-depth literature review in this area, we relied on the survey data to prototype a Learning Analytics dashboard (https://dashboard.socialmediadata.org/educhat). Our online dashboard uses a simple, easy-to-read interface in accordance with previous successful dashboard implementations. Graphical visualizations allow instructors to monitor discussion patterns, such as the frequency and times of posting. Visual content breakdowns by number of retweets, original posts, and topics in the form of hashtags and named entities reveal the constituents of students’ posts. The dashboard provides additional analysis in the form of sentiment and subjectivity ranking as a way to contextually aid qualitative assessment. To support instructors’ awareness of class participation, we incorporated two visualizations that highlight the most active users and individuals who are most frequently mentioned in others’ tweets. Instructors can use the dashboard to gauge the participation at the individual- or classroom-level, and further discover what topics and links students discuss and share on Twitter. Three instructors piloted the LA dashboard over a 4-month semester in the Fall of 2017. Following their use, we conducted evaluation interviews with these instructors. Instructor evaluations confirmed that the proposed design is aligned with their pedagogical needs; they favored an intuitive interface that combined summative metrics for the entire class and personalized assessment of individual students. Based on instructors’ feedback, our future work will iteratively refine the design by integrating additional interactive features to adjust time scales of the output, investigate source data, collect data from lists of Twitter users (as opposed to a single hashtag), and further integrate the dashboard with other LMS (Learning Management System) data.

scholarly journals Levels of Annotation in the Slovene Training Corpus ssj500k 2.2

2019 ◽  
Vol 70 (2) ◽  
pp. 390-399
Author(s):  
Mija Bon ◽  
Polona Gantar
Keyword(s):  
Semantic Role Labeling ◽  
Lexical Database ◽  
Named Entities ◽  
Training Corpus ◽  
Part Of Speech Tagging ◽  
Part Of Speech ◽  
Sentence Segmentation ◽  
The Individual ◽  
Syntactic Dependencies ◽  
Future Work

Abstract This paper presents the Slovene Training Corpus ssj500k 2.2, which has been annotated on the levels of tokenization, sentence segmentation, part-of-speech tagging, lemmatization, syntactic dependencies, named entities, verbal multi-word expressions, and semantic role labeling. It describes the individual layers of annotation and shows the scope of using the training corpus in the production of various lexicons, such as the lexicon of multi-word units and the valency lexicon of modern Slovene. It concludes by presenting our future work, i.e. the annotation of multi-word expressions based on the Slovene Lexical Database.

scholarly journals An Analysis of Sport-Specific Pain Symptoms through Inter-Individual Training Differences in CrossFit

Sports ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 68
Author(s):  
Maria Bernstorff ◽  
Norman Schumann ◽  
Nader Maai ◽  
Thomas Schildhauer ◽  
Matthias Königshausen
Keyword(s):  
Online Survey ◽  
Personal Information ◽  
Gluteus Medius ◽  
Single Type ◽  
Training Methods ◽  
Personal Training ◽  
Muscle Groups ◽  
Small Muscle ◽  
The Individual ◽  
Pain Symptoms

Background: CrossFit is one of the fastest growing “high-intensity functional training” methods in recent years. Due to the very demanding motion sequences and high loads, it was initially assumed that there was an extremely high risk of injury. However, studies have shown that injury rates are given between 0.74–3.3 per 1000 h of training, which is not higher than in other individual sports such as weightlifting. The purpose of the study was to estimate the type of pain symptoms that are directly related to CrossFit, to estimate the frequency of injuries that occur within a population of recreational CrossFit athletes, and, finally, to identify the factors influencing the frequency of pain during CrossFit training. Methods: A total of 414 active CrossFit athletes completed an online survey inclusive of 29 items focusing on individual physical characteristics and training behavior, as well as simultaneous or previously practiced sports. Results: There was a significantly higher proportion of knee pain in athletes who had previously or simultaneously played another sport (p = 0.014). The duration, intensity, or type of personal training plan developed, along with personal information such as age, gender, or BMI, had no significant influence on the pain data. We could not find any significant variance between the groups that we formed based on the differently stated one-repetition max (RMs). There were differences in athletes who stated that they did specific accessory exercises for small muscle groups. Above all, athletes performing exercises for the hamstrings and the gluteus medius indicated fewer pain symptoms for the sacro-iliac joint (SIJ)/iliac and lower back locations. Conclusions: It is important not to see CrossFit as a single type of sport. When treating a CrossFit athlete, care should be taken to address inter-individual differences. This underlines the significant differences of this study between the individual athletes with regard to the ability to master certain skills or their previous sporting experience. The mere fact of mastering certain exercises seems to lead to significantly more pain in certain regions. In addition, there seems to be a connection between the previous or simultaneous participation in other sports and the indication of pain in the knee region.

EVA 2.0: Emotional and rational multimodal argumentation between virtual agents

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Niklas Rach ◽  
Klaus Weber ◽  
Yuchi Yang ◽  
Stefan Ultes ◽  
Elisabeth André ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
User Feedback ◽  
Virtual Agents ◽  
Multi Agent System ◽  
Dialogue Game ◽  
Multi Agent ◽  
The Individual ◽  
Minimal Bias ◽  
Intuitive Interface ◽  
Emotional Level

Abstract Persuasive argumentation depends on multiple aspects, which include not only the content of the individual arguments, but also the way they are presented. The presentation of arguments is crucial – in particular in the context of dialogical argumentation. However, the effects of different discussion styles on the listener are hard to isolate in human dialogues. In order to demonstrate and investigate various styles of argumentation, we propose a multi-agent system in which different aspects of persuasion can be modelled and investigated separately. Our system utilizes argument structures extracted from text-based reviews for which a minimal bias of the user can be assumed. The persuasive dialogue is modelled as a dialogue game for argumentation that was motivated by the objective to enable both natural and flexible interactions between the agents. In order to support a comparison of factual against affective persuasion approaches, we implemented two fundamentally different strategies for both agents: The logical policy utilizes deep Reinforcement Learning in a multi-agent setup to optimize the strategy with respect to the game formalism and the available argument. In contrast, the emotional policy selects the next move in compliance with an agent emotion that is adapted to user feedback to persuade on an emotional level. The resulting interaction is presented to the user via virtual avatars and can be rated through an intuitive interface.

scholarly journals Comparative physical activity as a global question to assess physical activity among university students

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Katharina Diehl ◽  
Alessia Brassat ◽  
Jennifer Hilger-Kolb
Keyword(s):  
Physical Activity ◽  
University Students ◽  
Online Survey ◽  
Group Level ◽  
Comparative Measurement ◽  
Cross Sectional ◽  
Physically Active ◽  
Comparative Optimism ◽  
Individual Assessment ◽  
The Individual

Abstract Background To assess physical activity (PA), a comparative measurement – evaluating one’s own PA compared to others – may be an appropriate method. In previous studies, the use of comparative measurements led to an effect known as unrealistic comparative optimism (UCO) – people being unrealistically optimistic about their behavior. Our aim was to use this comparative measurement in university students to quantify the prevalence of UCO at the group level and to draw conclusions on its validity. Methods We used data from the Nutrition and Physical Activity in Adolescence Study (NuPhA), a cross-sectional online survey that included only self-reports (n = 689). To assess PA among students, they were asked to rate their PA level compared to that of their same-aged fellow students. In addition, we used the Godin-Shephard leisure-time PA questionnaire and other questions on PA for comparisons. We used bivariate and cluster-based analyses to identify potential UCO. Results We found that UCO at the group level led to an uneven distribution, with a higher proportion of students who rated themselves as being more physically active than average. However, the individual assessment of PA with a single and simple comparative question seemed to be valid. Discussion A global single comparative question seems useful for studies where PA is measured as a covariate in university students.

Flexibility Effects in a Single Link Robotic Manipulator

1993 ◽  
Author(s):  
C. Nataraj
Keyword(s):  
Large Scale ◽  
Robotic Manipulator ◽  
Flexible Beam ◽  
Rotating Speed ◽  
Weighted Residuals ◽  
Individual Interaction ◽  
Single Link ◽  
Rigid Mass ◽  
The Individual ◽  
Future Work

Abstract A single link robotic manipulator is modeled as a rotating flexible beam with a rigid mass at the tip and accurate energy expressions are derived. The resulting partial differential equations are solved using an approximate method of weighted residuals. From the solutions, coupling between axial and flexural deformations and the interactions with rigid body motions are rigorously analyzed. The emphasis in the current paper is not on an exhaustive analysis of existing systems but it is rather intended to compare and highlight the various flexibility effects in a relatively simple system. Hence, a nondimensional parametric analysis is performed to determine the effect of several parameters (including the rotating speed) on the errors and the individual interaction effects are discussed. Comparison with previous work in the field shows important phenomena often ignored or buried in large scale numerical analyses. Future work including application to multi-link robots is outlined.

The influence of culture on consumer perceptions of deceptiveness

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Haithem Zourrig ◽  
Mengxia Zhang ◽  
Kamel El Hedhli ◽  
Imene Becheur
Keyword(s):  
Culturally Diverse ◽  
Online Survey ◽  
Consumer Perceptions ◽  
Chinese Consumers ◽  
Content Type ◽  
Individual Level ◽  
Information Manipulation ◽  
Societal Level ◽  
The Individual ◽  
Situational Constraint

Purpose This study aims to apply McCornack’s (1992) information manipulation theory to the context of fraud and investigates the effects of culture on perceived deceptiveness. Design/methodology/approach In total, 400 Chinese consumers and an equal-size sample of Canadian consumers were recruited to fill an online survey. The survey integrates four scenarios of insurance fraud and measures of perceived deceptiveness, cultural tightness and horizontal-vertical idiocentrism allocentrism, in addition to some control variables. Findings Results show that at the societal level of culture, perceived deceptiveness is higher in individualistic than in collectivistic cultures. When accounting for the level of situational constraint, cultural tightness was found to magnify the perceived deceptiveness. At the individual level of culture, vertical-allocentrism and vertical-idiocentrism were found to weigh against the perception of deceptiveness. Originality/value Understanding cultural differences in perceived deceptiveness is helpful to spot sources of consumers’ vulnerability to fraud tolerance among a culturally diverse public.

Dynamic roles of social presence and individual differences in social TV platforms

2021 ◽  
pp. 135485652110575
Author(s):  
Jihyun Kim ◽  
Kelly Merrill
Keyword(s):  
Individual Differences ◽  
Social Presence ◽  
Online Survey ◽  
Unique Form ◽  
Tv Viewing ◽  
Television Content ◽  
Social Tv ◽  
The Social ◽  
Private And Public ◽  
The Individual

These days, many individuals engage in a unique form of TV viewing that includes a simultaneous act of watching television content and talking about it with others in a mediated environment. This phenomenon is commonly referred to as social TV viewing. Responding to the popularity of this form of TV viewing behavior, the present study examines the individual differences of the social TV viewing experience, particularly with regard to different communication platforms (e.g. private vs. public). Based on the data collected from an online survey, primary findings indicate that extroverted and lonely individuals have different social TV viewing experiences such as preferences for a particular type of platforms for social TV viewing. Further, social presence plays an important role in the understanding of social TV enjoyment in private and public platforms.

scholarly journals Contextual Determinants of Employee Entrepreneurial Behavior in Support of Corporate Entrepreneurship: A Systematic Review and Research Agenda

2018 ◽  
Vol 26 (03) ◽  
pp. 285-326 ◽  
Author(s):  
Michael Mustafa ◽  
Fiona Gavin ◽  
Mathew Hughes
Keyword(s):  
Corporate Entrepreneurship ◽  
Research Field ◽  
Complex Nature ◽  
Contextual Influences ◽  
Entrepreneurial Behavior ◽  
Firm Level ◽  
Contextual Determinants ◽  
The Individual ◽  
Job Role ◽  
Future Work

The individual entrepreneurial behavior of employees represents one of the primary antecedents of Corporate Entrepreneurship. The complex nature of ‘employee entrepreneurial behavior’ suggests that a myriad of contextual influences act on the emergence of such behavior. It is imperative that theorists and practitioners alike understand both the subtle and sophisticated ways in which context influences employee entrepreneurial behavior. To address these issues and encourage future work, this study performs a systematic literature review to provide an overview of the field and examines the influence of the job/role, organizational/work and external contexts on employee entrepreneurial behavior. Findings suggest that employee entrepreneurial behavior is an emergent research field and that its behaviors can manifest themselves in different ways compared to firm-level entrepreneurial behaviors. We also show the sophisticated manner in which different types of context influence employee entrepreneurial behavior.

scholarly journals A cross-sectional study of the use and effectiveness of the Individual Development Plan among doctoral students

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 722 ◽  
Author(s):  
Nathan L. Vanderford ◽  
Teresa M. Evans ◽  
L. Todd Weiss ◽  
Lindsay Bira ◽  
Jazmin Beltran-Gastelum
Keyword(s):  
Career Development ◽  
Doctoral Students ◽  
Online Survey ◽  
Career Planning ◽  
Statistical Significance ◽  
Development Plan ◽  
Individual Development ◽  
Negative Consequences ◽  
Cross Sectional ◽  
The Individual

Background: The Individual Development Plan (IDP) was introduced as a tool to aid in career planning for doctoral trainees. Despite the National Institutes of Health and academic institutions creating policies that mandate the use of IDPs, little information exists regarding the use and effectiveness of the career planning tool. Methods: We conducted a multi-institutional, online survey to measure IDP use and effectiveness. The survey was distributed to potential respondents via social media and direct email. IDP survey questions were formatted using a five-point Likert scale (strongly agree, agree, neutral, disagree and strongly disagree). For data analysis purposes, responses were grouped into two categories (agree versus does not agree/disagree). The data were summarized as one-way frequencies and the Pearson chi-square test was used to determine the statistical significance of univariate associations between the survey variables and an outcome measure of the effectiveness of the IDP. Results: Among all respondents, fifty-three percent reported that they are required to complete an IDP while thirty-three percent reported that the tool is helpful to their career development. Further, our data suggests that the IDP is most effective when doctoral students complete the tool with faculty mentors with whom they have a positive relationship. Respondents who are confident about their career plans and who take advantage of career development resources at their institution are also more likely to perceive that the IDP is useful for their career development. Conclusion: Given the nuanced use and effectiveness of the IDP, we call for additional research to characterize the overall use and effectiveness of the IDP and to determine whether there are unintended negative consequences created through the use of the tool. Furthermore, we recommend an enhancement of career development infrastructure that would include mentorship training for faculty in order to provide substantially more career planning support to trainees.

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