Exploring Library Core Competencies: A Text Mining Study of American Library Association’s Job Advertisements From 2006 Through 2017

2021 ◽  
pp. 089443932110272
Author(s):  
Qinghong Yang ◽  
Zehong Shi ◽  
Yan Quan Liu
Keyword(s):  
Language Processing ◽  
Work Experience ◽  
Core Competencies ◽  
Core Competency ◽  
Analytical Investigation ◽  
Market Demand ◽  
American Library ◽  
Job Titles ◽  
Job Advertisements ◽  
Processing Techniques

Are core competency requirements for relevant positions in the library shifting? Applying natural language processing techniques to understand the current market demand for core competencies, this study explores job advertisements issued by the American Library Association (ALA) from 2006 to 2017. Research reveals that the job demand continues to rise at a rate of 13% (2006–2017) and that the requirements for work experience are substantially extended, diversity of job titles becomes prevalent, and rich service experience and continuous lifelong learning skills are becoming more and more predominant for librarians. This analytical investigation informs the emerging demands in the American job market debriefing the prioritization and reprioritization of the current core competency requirements for ALA librarians.

scholarly journals Current Market Demand for Core Competencies of Librarianship—A Text Mining Study of American Library Association’s Advertisements from 2009 through 2014

2016 ◽  
Vol 6 (2) ◽  
pp. 48 ◽  
Author(s):  
Qinghong Yang ◽  
Xingzhi Zhang ◽  
Xiaoping Du ◽  
Arlene Bielefield ◽  
Yan Liu
Keyword(s):  
Text Mining ◽  
Core Competencies ◽  
Market Demand ◽  
American Library

An Input–Process–Output Model of Pilot Core Competencies

2017 ◽  
Vol 7 (2) ◽  
pp. 78-85 ◽  
Author(s):  
Heikki Mansikka ◽  
Don Harris ◽  
Kai Virtanen
Keyword(s):  
Path Analysis ◽  
Team Performance ◽  
Core Competencies ◽  
Core Competency ◽  
Principal Component ◽  
Analysis Model ◽  
Input Process ◽  
The Core ◽  
Performance Framework ◽  
Process Output

Abstract. The aim of this study was to investigate the relationship between the flight-related core competencies for professional airline pilots and to structuralize them as components in a team performance framework. To achieve this, the core competency scores from a total of 2,560 OPC (Operator Proficiency Check) missions were analyzed. A principal component analysis (PCA) of pilots’ performance scores across the different competencies was conducted. Four principal components were extracted and a path analysis model was constructed on the basis of these factors. The path analysis utilizing the core competencies extracted adopted an input–process–output’ (IPO) model of team performance related directly to the activities on the flight deck. The results of the PCA and the path analysis strongly supported the proposed IPO model.

scholarly journals Does higher education properly prepare graduates for the growing artificial intelligence market? Gaps identification using text mining

2021 ◽  
pp. 1-13
Author(s):  
Lamiae Benhayoun ◽  
Daniel Lang
Keyword(s):  
Artificial Intelligence ◽  
Natural Language Processing ◽  
Text Mining ◽  
Natural Language ◽  
Language Processing ◽  
Academic Training ◽  
Market Requirements ◽  
Job Advertisements ◽  
The Individual

BACKGROUND: The renewed advent of Artificial Intelligence (AI) is inducing profound changes in the classic categories of technology professions and is creating the need for new specific skills. OBJECTIVE: Identify the gaps in terms of skills between academic training on AI in French engineering and Business Schools, and the requirements of the labour market. METHOD: Extraction of AI training contents from the schools’ websites and scraping of a job advertisements’ website. Then, analysis based on a text mining approach with a Python code for Natural Language Processing. RESULTS: Categorization of occupations related to AI. Characterization of three classes of skills for the AI market: Technical, Soft and Interdisciplinary. Skills’ gaps concern some professional certifications and the mastery of specific tools, research abilities, and awareness of ethical and regulatory dimensions of AI. CONCLUSIONS: A deep analysis using algorithms for Natural Language Processing. Results that provide a better understanding of the AI capability components at the individual and the organizational levels. A study that can help shape educational programs to respond to the AI market requirements.

scholarly journals Twitter Sentiment Analysis towards COVID-19 Vaccines in the Philippines Using Naïve Bayes

Information ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 204
Author(s):  
Charlyn Villavicencio ◽  
Julio Jerison Macrohon ◽  
X. Alphonse Inbaraj ◽  
Jyh-Horng Jeng ◽  
Jer-Guang Hsieh
Keyword(s):  
Sentiment Analysis ◽  
Language Processing ◽  
Data Science ◽  
Naive Bayes ◽  
The Philippines ◽  
Naïve Bayes ◽  
Social Networking Site ◽  
Bayes Model ◽  
The Government ◽  
Processing Techniques

A year into the COVID-19 pandemic and one of the longest recorded lockdowns in the world, the Philippines received its first delivery of COVID-19 vaccines on 1 March 2021 through WHO’s COVAX initiative. A month into inoculation of all frontline health professionals and other priority groups, the authors of this study gathered data on the sentiment of Filipinos regarding the Philippine government’s efforts using the social networking site Twitter. Natural language processing techniques were applied to understand the general sentiment, which can help the government in analyzing their response. The sentiments were annotated and trained using the Naïve Bayes model to classify English and Filipino language tweets into positive, neutral, and negative polarities through the RapidMiner data science software. The results yielded an 81.77% accuracy, which outweighs the accuracy of recent sentiment analysis studies using Twitter data from the Philippines.

scholarly journals Shall I Work with Them? A Knowledge Graph-Based Approach for Predicting Future Research Collaborations

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 664
Author(s):  
Nikos Kanakaris ◽  
Nikolaos Giarelis ◽  
Ilias Siachos ◽  
Nikos Karacapilidis
Keyword(s):  
Language Processing ◽  
Scientific Knowledge ◽  
Link Prediction ◽  
Performance Metrics ◽  
Future Research ◽  
Knowledge Graph ◽  
Prediction Problem ◽  
Textual Information ◽  
Research Collaborations ◽  
Processing Techniques

We consider the prediction of future research collaborations as a link prediction problem applied on a scientific knowledge graph. To the best of our knowledge, this is the first work on the prediction of future research collaborations that combines structural and textual information of a scientific knowledge graph through a purposeful integration of graph algorithms and natural language processing techniques. Our work: (i) investigates whether the integration of unstructured textual data into a single knowledge graph affects the performance of a link prediction model, (ii) studies the effect of previously proposed graph kernels based approaches on the performance of an ML model, as far as the link prediction problem is concerned, and (iii) proposes a three-phase pipeline that enables the exploitation of structural and textual information, as well as of pre-trained word embeddings. We benchmark the proposed approach against classical link prediction algorithms using accuracy, recall, and precision as our performance metrics. Finally, we empirically test our approach through various feature combinations with respect to the link prediction problem. Our experimentations with the new COVID-19 Open Research Dataset demonstrate a significant improvement of the abovementioned performance metrics in the prediction of future research collaborations.

scholarly journals A Natural Language Processing Approach to Measuring Treatment Adherence and Consistency Using Semantic Similarity

AERA Open ◽  
2021 ◽  
Vol 7 ◽  
pp. 233285842110286
Author(s):  
Kylie L. Anglin ◽  
Vivian C. Wong ◽  
Arielle Boguslav
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Semantic Similarity ◽  
Language Processing ◽  
Intervention Implementation ◽  
Proof Of Concept ◽  
Coaching Intervention ◽  
Processing Techniques ◽  
Teacher Coaching ◽  
The Impact

Though there is widespread recognition of the importance of implementation research, evaluators often face intense logistical, budgetary, and methodological challenges in their efforts to assess intervention implementation in the field. This article proposes a set of natural language processing techniques called semantic similarity as an innovative and scalable method of measuring implementation constructs. Semantic similarity methods are an automated approach to quantifying the similarity between texts. By applying semantic similarity to transcripts of intervention sessions, researchers can use the method to determine whether an intervention was delivered with adherence to a structured protocol, and the extent to which an intervention was replicated with consistency across sessions, sites, and studies. This article provides an overview of semantic similarity methods, describes their application within the context of educational evaluations, and provides a proof of concept using an experimental study of the impact of a standardized teacher coaching intervention.

scholarly journals Empathy Can Be Taught, and Patients Teach it Best

2021 ◽  
Vol 8 ◽  
pp. 238212052110003
Author(s):  
Sudhagar Thangarasu ◽  
Gowri Renganathan ◽  
Piruthiviraj Natarajan
Keyword(s):  
Medical Education ◽  
Graduate Medical Education ◽  
Core Competencies ◽  
Core Competency ◽  
Role Modeling ◽  
Residency Programs ◽  
Graduate Medical ◽  
Mixed Messages ◽  
Attending Physicians ◽  
Medical Education Curriculum

Empathy toward patients is an essential skill for a physician to deliver the best care for any patient. Empathy also protects the physician from moral injury and decreases the chances for malpractice litigations. The current graduate medical education curriculum allows trainees to graduate without getting focused training to develop empathy as a core competency domain. The tools to measure empathy inherently lack validity. The accurate measure of the provider’s empathy comes from the patient’s perspectives of their experience and their feedback, which is rarely reaching the trainee. The hidden curriculum in residency programs gives mixed messages to trainees due to inadequate role modeling by attending physicians. This narrative style manuscript portrays a teachable moment at the bedside vividly. The teaching team together reflected upon the lack of empathy, took steps to resolve the issue. The attending demonstrated role modeling as an authentic and impactful technique to teach empathy. The conclusion includes a proposal to include the patient’s real-time feedback to trainees as an essential domain under Graduate Medical Education core competencies of professionalism and patient care.

Compansion: From research prototype to practical integration

1998 ◽  
Vol 4 (1) ◽  
pp. 73-95 ◽  
Author(s):  
KATHLEEN F. MCCOY ◽  
CHRISTOPHER A. PENNINGTON ◽  
ARLENE LUBEROFF BADMAN
Keyword(s):  
Language Processing ◽  
Augmentative And Alternative Communication ◽  
Communication Aids ◽  
Alternative Communication ◽  
Communicative Ability ◽  
Linguistic Ability ◽  
Research Prototype ◽  
Intelligent Communication ◽  
Processing Techniques ◽  
Parser Generator

Augmentative and Alternative Communication (AAC) is the field of study concerned with providing devices and techniques to augment the communicative ability of a person whose disability makes it difficult to speak or otherwise communicate in an understandable fashion. For several years, we have been applying natural language processing techniques to the field of AAC to develop intelligent communication aids that attempt to provide linguistically correct output while increasing communication rate. Previous effort has resulted in a research prototype called Compansion that expands telegraphic input. In this paper we describe that research prototype and introduce the Intelligent Parser Generator (IPG). IPG is intended to be a practical embodiment of the research prototype aimed at a group of users who have cognitive impairments that affect their linguistic ability. We describe both the theoretical underpinnings of Compansion and the practical considerations in developing a usable system for this population of users.

scholarly journals The Trending Academic Library Job Market: An Analysis of Library Position Announcements from 2011 with Comparisons to 1996 and 1988

2015 ◽  
Vol 76 (6) ◽  
pp. 716-739 ◽  
Author(s):  
Therese F. Triumph ◽  
Penny M. Beile
Keyword(s):  
Work Experience ◽  
Academic Library ◽  
The United States ◽  
Primary Objective ◽  
Job Market ◽  
Current State ◽  
Emerging Trends ◽  
Job Advertisements ◽  
Salary Information ◽  
Over Time

The primary objective of the study was to describe the number, types and titles, requested qualifications and skills, salary information, and locations of positions advertised in 2011 on the ALA JobLIST and ARL Job Announcements websites and in the print version of the Chronicle of Higher Education for purposes of determining the current state of the academic library job market in the United States. To investigate changes in the academic library job market and identify emerging trends over a 23-year period, results also were compared to studies that analyzed position announcements from 1996 and 1988. Content analysis of 957 unique academic library job advertisements revealed relative stasis in the market regarding the number of positions advertised, presence of administrative duties, geographic distribution of positions, and, to some extent, educational requirements. However, other comparisons were more dynamic. Specifically, there has been a decline in foreign language skills and prior work experience requirements over time while computer skills are increasingly sought. Perhaps most striking is the proliferation of new position titles that have emerged over time, which serves as an indication that library positions are becoming increasingly specialized.

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