scholarly journals Towards Automatic Collaboration Analytics for Group Speech Data Using Learning Analytics

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3156
Author(s):  
Sambit Praharaj ◽  
Maren Scheffel ◽  
Marcel Schmitz ◽  
Marcus Specht ◽  
Hendrik Drachsler
Keyword(s):  
Learning Analytics ◽  
Field Trials ◽  
Sensor Technology ◽  
Centrality Measures ◽  
Network Graph ◽  
Word Level ◽  
Significant Step ◽  
Audio Data ◽  
Group Members ◽  
Level Analysis

Collaboration is an important 21st Century skill. Co-located (or face-to-face) collaboration (CC) analytics gained momentum with the advent of sensor technology. Most of these works have used the audio modality to detect the quality of CC. The CC quality can be detected from simple indicators of collaboration such as total speaking time or complex indicators like synchrony in the rise and fall of the average pitch. Most studies in the past focused on “how group members talk” (i.e., spectral, temporal features of audio like pitch) and not “what they talk”. The “what” of the conversations is more overt contrary to the “how” of the conversations. Very few studies studied “what” group members talk about, and these studies were lab based showing a representative overview of specific words as topic clusters instead of analysing the richness of the content of the conversations by understanding the linkage between these words. To overcome this, we made a starting step in this technical paper based on field trials to prototype a tool to move towards automatic collaboration analytics. We designed a technical setup to collect, process and visualize audio data automatically. The data collection took place while a board game was played among the university staff with pre-assigned roles to create awareness of the connection between learning analytics and learning design. We not only did a word-level analysis of the conversations, but also analysed the richness of these conversations by visualizing the strength of the linkage between these words and phrases interactively. In this visualization, we used a network graph to visualize turn taking exchange between different roles along with the word-level and phrase-level analysis. We also used centrality measures to understand the network graph further based on how much words have hold over the network of words and how influential are certain words. Finally, we found that this approach had certain limitations in terms of automation in speaker diarization (i.e., who spoke when) and text data pre-processing. Therefore, we concluded that even though the technical setup was partially automated, it is a way forward to understand the richness of the conversations between different roles and makes a significant step towards automatic collaboration analytics.

scholarly journals A Phonetic Complexity-Based Approach for Intelligibility and Articulatory Precision Testing: A Preliminary Study on Talkers With Amyotrophic Lateral Sclerosis

2018 ◽  
Vol 61 (9) ◽  
pp. 2205-2214 ◽  
Author(s):  
Mili Kuruvilla-Dugdale ◽  
Claire Custer ◽  
Lindsey Heidrick ◽  
Richard Barohn ◽  
Raghav Govindarajan
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Speech Intelligibility ◽  
Speech Impairments ◽  
Word Level ◽  
Preliminary Study ◽  
Perceived Impact ◽  
Complex Words ◽  
Level Analysis ◽  
Precision Testing ◽  
Lateral Sclerosis

Purpose This study describes a phonetic complexity-based approach for speech intelligibility and articulatory precision testing using preliminary data from talkers with amyotrophic lateral sclerosis. Method Eight talkers with amyotrophic lateral sclerosis and 8 healthy controls produced a list of 16 low and high complexity words. Sixty-four listeners judged the samples for intelligibility, and 2 trained listeners completed phoneme-level analysis to determine articulatory precision. To estimate percent intelligibility, listeners orthographically transcribed each word, and the transcriptions were scored as being either accurate or inaccurate. Percent articulatory precision was calculated based on the experienced listeners' judgments of phoneme distortions, deletions, additions, and/or substitutions for each word. Articulation errors were weighted based on the perceived impact on intelligibility to determine word-level precision. Results Between-groups differences in word intelligibility and articulatory precision were significant at lower levels of phonetic complexity as dysarthria severity increased. Specifically, more severely impaired talkers showed significant reductions in word intelligibility and precision at both complexity levels, whereas those with milder speech impairments displayed intelligibility reductions only for more complex words. Articulatory precision was less sensitive to mild dysarthria compared to speech intelligibility for the proposed complexity-based approach. Conclusions Considering phonetic complexity for dysarthria tests could result in more sensitive assessments for detecting and monitoring dysarthria progression.

scholarly journals Revision and Participation Patterns in Grades 5 and 6 Wiki Writing

2016 ◽  
Vol 18 (1) ◽  
pp. 110
Author(s):  
Christine Portier ◽  
Shelley Stagg Peterson
Keyword(s):  
Social Studies ◽  
Writing Groups ◽  
Middle Grade ◽  
Action Research Project ◽  
Word Level ◽  
Willingness To Change ◽  
Working Together ◽  
Group Members ◽  
Group Member

Our study examined middle grade students’ participation in wikis during their two-month social studies unit co-taught by two teachers as part of a larger action research project. Using an analysis of 42 grades 5 and 6 students working together in eight wiki writing groups, we report on the frequency and types of revisions they made to collaboratively-written essays, and the distribution of the workload across group members in each of the wiki groups. Discussion data with 16 students from these wiki groups helps contextualize our analysis.Our findings suggest that given their extended time to write, students revised frequently, making replacements more often than they deleted, added or moved content. Students indicated a willingness to change others’ contributions and to have their own contributions revised by others in order to improve the quality of the essays. The majority of their revisions were at the word level, rather than at sentence, paragraph, and whole-text levels. One student in each group contributed significantly more frequently than any other group member. There were no gender or grade patterns in the frequencies or types of contributions that students made to the wikis.

scholarly journals Assessment of Technological Developments in Data Analytics for Sensor-Based and Robot Sorting Plants Based on Maturity Levels to Improve Austrian Waste Sorting Plants

2021 ◽  
Vol 13 (16) ◽  
pp. 9472
Author(s):  
Karl Friedrich ◽  
Theresa Fritz ◽  
Gerald Koinig ◽  
Roland Pomberger ◽  
Daniel Vollprecht
Keyword(s):  
Waste Management ◽  
Value Chain ◽  
Data Analytics ◽  
Building Materials ◽  
Sensor Technology ◽  
Significant Step ◽  
Extended Value ◽  
Technological Developments ◽  
Set Up ◽  
Sensor Based Sorting

Sensor-based and robot sorting are key technologies in the extended value chain of many products such as packaging waste (glass, plastics) or building materials since these processes are significant contributors in reaching the EU recycling goals. Hence, technological developments and possibilities to improve these processes concerning data analytics are evaluated with an interview-based survey. The requirements to apply data analytics in sensor-based sorting are separated into different sections, i.e., data scope or consistency. The interviewed companies are divided into four categories: sorting machine manufacturers, sorting robot manufacturers, recycling plant operators, and sensor technology companies. This paper aims to give novel insights into the degree of implementation of data analytics in the Austrian waste management sector. As a result, maturity models are set up for these sections and evaluated for each of the interview partner categories. Interviewees expressed concerns regarding the implementation such as a perceived loss of control and, subsequently, a supposed inability to intervene. Nevertheless, further comments by the interviewees on the state of the waste management sector conveyed that data analytics in their processes would also be a significant step forward to achieve the European recycling goals.

scholarly journals Festival community networks and transformative place-making

2018 ◽  
Vol 11 (3) ◽  
pp. 335-349 ◽  
Author(s):  
David Jarman
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Centrality Measures ◽  
Structured Interviews ◽  
Place Making ◽  
Dual Nature ◽  
Content Type ◽  
Attribute Data ◽  
Group Members

Purpose Festivals are often explicitly connected to the destinations in which they take place, explored here as contributing to broader processes of place-making and engagement with local communities. Place is defined at a local scale, primarily as experienced by volunteer contributors to an arts and cultural festival in urban Scotland. Networked relationships between festival volunteers inform the research methods and analysis, reflecting both observer and insider perspectives. This paper aims to comment on varying attitudes among the contributors, relating these findings to their positions in the festival’s social network. Design/methodology/approach Social network analysis methods were used to capture and examine data from a sample of festival volunteers: a survey instrument was distributed among individuals identified by the creative director, acting as a key informant. These data generated information on connections between the respondents, as well as demographic and opinion-based attribute data. Network centrality measures were used to sample the respondents for four follow-up interviews with festival volunteers. Findings The resulting network revealed a core-periphery structure to the festival’s organising team. The influential core group members were more established volunteers, recognised for their value to the team. The festival was widely endorsed as contributing to local place-making, though not uncritically. Management implications were identified for the dual nature of the festival organisation: a formal hierarchy with clear functional departments, acting as a platform for an intangible yet vital social network. Originality/value Social relationships are shown to have profound implications for the management and identity of this volunteer festival, in relation to its host neighbourhood. Combining social network analysis with semi-structured interviews has demonstrated the value of this mixed methods approach.

In search of the true group animal: the effects of affiliation orientation and social comparison orientation upon group satisfaction

2005 ◽  
Vol 19 (1) ◽  
pp. 69-81 ◽  
Author(s):  
Bram P. Buunk ◽  
Aukje Nauta ◽  
Eric Molleman
Keyword(s):  
Social Comparison ◽  
Undergraduate Students ◽  
Big Five Personality ◽  
Individual Level ◽  
Group Satisfaction ◽  
Social Comparison Orientation ◽  
Group Members ◽  
High Level ◽  
True Group ◽  
Level Analysis

A study among 653 undergraduate students examined the effects upon group satisfaction of social comparison orientation (Gibbons & Buunk, 1999) and affiliation orientation, i.e. the preference for doing things together and in groups versus a preference for doing things alone. Affiliation orientation correlated positively with extraversion and agreeableness, and social comparison orientation correlated negatively with emotional stability and openness to experience. A multi‐level analysis showed that individual level variance in group satisfaction was explained by an interaction effect of affiliation orientation and social comparison orientation: a high level of affiliation orientation was associated with high group satisfaction of individual group members, but only among those low in social comparison orientation. Among those high in social comparison orientation, a high level of affiliation orientation was even associated, though not very strongly, with low group satisfaction. These effects were upheld when simultaneously controlling for all ‘Big Five’ personality dimensions. It was concluded that the typical ‘group animal’ is someone who has a strong preference for affiliation, combined with a low tendency to compare him‐ or herself with others. Copyright © 2005 John Wiley & Sons, Ltd.

scholarly journals Application of Formal Word-Level Analysis to Constrained Random Simulation

2008 ◽  
pp. 487-490 ◽  
Author(s):  
Hyondeuk Kim ◽  
Hoonsang Jin ◽  
Kavita Ravi ◽  
Petr Spacek ◽  
John Pierce ◽  
...  
Keyword(s):  
Random Simulation ◽  
Word Level ◽  
Level Analysis

scholarly journals Informing learning design through analytics: Applying network graph analysis

2018 ◽  
Vol 34 (2) ◽  
Author(s):  
Dirk Ifenthaler ◽  
David Gibson ◽  
Eva Dobozy
Keyword(s):  
Learning Environments ◽  
Learning Analytics ◽  
Graph Analysis ◽  
Learning Design ◽  
Digital Learning ◽  
Time Data ◽  
Network Graph ◽  
Dynamic Learning ◽  
The Impact

Learning design has traditionally been thought of as an activity occurring prior to the presentation of a learning experience or a description of that activity. With the advent of near real-time data and new opportunities of representing the decisions and actions of learners in digital learning environments, learning designers can now apply dynamic learning analytics information on the fly in order to evaluate learner characteristics, examine learning designs, analyse the effectiveness of learning materials and tasks, adjust difficulty levels, and measure the impact of interventions and feedback. In a case study with 3550 users, the navigation sequence and network graph analysis demonstrate a potential application of learning analytics design. Implications based on the case study show that integration of analytics data into the design of learning environments is a promising approach.

scholarly journals Measuring Machine Translation Errors in New Domains

2013 ◽  
Vol 1 ◽  
pp. 429-440 ◽  
Author(s):  
Ann Irvine ◽  
John Morgan ◽  
Marine Carpuat ◽  
Hal Daumé ◽  
Dragos Munteanu
Keyword(s):  
Machine Translation ◽  
Domain Adaptation ◽  
Future Research ◽  
Translation System ◽  
Medical Texts ◽  
Word Level ◽  
Machine Translation System ◽  
Measuring Machine ◽  
Translation Errors ◽  
Level Analysis

We develop two techniques for analyzing the effect of porting a machine translation system to a new domain. One is a macro-level analysis that measures how domain shift affects corpus-level evaluation; the second is a micro-level analysis for word-level errors. We apply these methods to understand what happens when a Parliament-trained phrase-based machine translation system is applied in four very different domains: news, medical texts, scientific articles and movie subtitles. We present quantitative and qualitative experiments that highlight opportunities for future research in domain adaptation for machine translation.

Tutorial: Assessment and Analysis of Polysyllables in Young Children

2018 ◽  
Vol 49 (1) ◽  
pp. 42-58 ◽  
Author(s):  
Sarah Masso ◽  
Sharynne McLeod ◽  
Elise Baker
Keyword(s):  
American English ◽  
Assessment Tools ◽  
Single Word ◽  
Clinical Value ◽  
Research Papers ◽  
Word Level ◽  
Analysis Methods ◽  
Clinical Tools ◽  
Level Analysis

Purpose Polysyllables, words of 3 or more syllables, represent almost 30% of words used in American English. The purpose of this tutorial is to support speech-language pathologists' (SLPs') assessment and analysis of polysyllables, extending the focus of published assessment tools that focus on sampling and analyzing children's segmental accuracy and/or the presence of phonological error patterns. Method This tutorial will guide SLPs through a review of 53 research papers that have explored the use of polysyllables in assessment, including the sampling and analysis procedures used in different research studies. The tutorial will also introduce two new tools to analyze and interpret polysyllable speech samples: the Word-Level Analysis of Polysyllables (WAP; Masso, 2016b) and the Framework of Polysyllable Maturity (Framework; Masso, 2016a). Results Connected speech and single-word sampling tasks were used across the 53 studies to elicit polysyllables, and a number of analysis methods were reported, including measures of segmental accuracy and measures of structural and suprasegmental accuracy. The WAP and the Framework extend SLPs' depth of analysis of polysyllables. Conclusion SLPs need a range of clinical tools to support the assessment and analysis of polysyllables. A case study comparing different speech analysis methods demonstrates the clinical value in utilizing the WAP and the Framework to interpret children's polysyllable productions in addition to traditional methods of speech sampling and analysis.

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