Which Learning Outcomes Should I Acquire? A Bar Chart-Based Semantic System for Visually Comparing Learners' Acquirements with Labor Market Requirements

The ability to plan a training path fulfilling working needs plays a key role, when it comes to finding the desired job. Nonetheless, in a dynamic scenario characterized by frequent technological innovations and economic changes, as the present one, getting a clear picture of the requirements of the world of work could become difficult, as it would imply performing a deep periodic evaluation of available job offers, and matching them with own previous experience. Intelligent systems able to automatically match résumés with job offers already exist, but they are mostly targeted to recruiters, instead of learners. This work aims at filling this gap, by presenting a system for comparing learners' acquirements - expressed in terms of learning outcomes - with companies requirements. The proposed system relies on semantics for processing natural language texts and exploits bar charts to visualize learning outcomes and their levels in order to quickly depict similarities and differences between résumés and job offers. An evaluation, on 50 volunteers, underlined the added value of the system.

[1]  Juha Paavola,et al.  STOPS: a graph-based study planning and curriculum development tool , 2014, Koli Calling.

[2]  P. Gestwicki Work in progress - curriculum visualization , 2008, 2008 38th Annual Frontiers in Education Conference.

[3]  Christopher D. Manning,et al.  Generating Typed Dependency Parses from Phrase Structure Parses , 2006, LREC.

[4]  Andrea Sanna,et al.  Job Recruitment and Job Seeking Processes: How Technology Can Help , 2014, IT Professional.

[5]  Hilary Dexter,et al.  An Ontology-Based Curriculum Knowledgebase for Managing Complexity and Change , 2009, 2009 Ninth IEEE International Conference on Advanced Learning Technologies.

[6]  Preston R. Aldrich,et al.  The curriculum prerequisite network: a tool for visualizing and analyzing academic curricula , 2014, ArXiv.

[7]  Andrea Sanna,et al.  A semantic matchmaking system for job recruitment , 2010, I-KNOW 2010.

[8]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[10]  Ron Zucker,et al.  ViCurriAS: a curriculum visualization tool for faculty, advisors, and students , 2009 .

[11]  Fabrizio Lamberti,et al.  A Semantic Recommender System for Adaptive Learning , 2015, IT Professional.

[12]  Janis Grundspenkis,et al.  Graph based framework and its implemented prototype for personalized study planning , 2013, 2013 Second International Conference on E-Learning and E-Technologies in Education (ICEEE).

[13]  Harri Siirtola,et al.  Interactive Curriculum Visualization , 2013, 2013 17th International Conference on Information Visualisation.

[14]  Hanspeter Pfister,et al.  LineUp: Visual Analysis of Multi-Attribute Rankings , 2013, IEEE Transactions on Visualization and Computer Graphics.

[15]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[16]  Lorenzo Sommaruga,et al.  Curriculum visualization in 3D , 2007, Web3D '07.

[17]  Colin Ware,et al.  Information Visualization: Perception for Design , 2000 .

[18]  W. Cleveland,et al.  Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods , 1984 .

[19]  Ted Pedersen,et al.  WordNet::Similarity - Measuring the Relatedness of Concepts , 2004, NAACL.

[20]  P. Meiksins,et al.  Changing contours of work : jobs and opportunities in the new economy , 2007 .

[21]  Jose Antonio Morán,et al.  Representation of a Course Structure Focused on Activities Using Information Visualization Techniques , 2011, 2011 IEEE 11th International Conference on Advanced Learning Technologies.

[22]  S. Yuan,et al.  StreamLiner: A General-Purpose Interactive Course-Visualization Tool , 2008, 2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop.

[23]  Simone Kriglstein Analysis of Ontology Visualization Techniques for Modular Curricula , 2008, USAB.