The Importance of Training Needs Analysis in Authoring Technology Enhanced Learning for Companies

2008 ◽  
pp. 107-134 ◽  
Author(s):  
Emma O’Brien ◽  
Timothy Hall ◽  
Kevin Johnson
Keyword(s):  
Content Management ◽  
Training Needs ◽  
Needs Analysis ◽  
Technology Enhanced Learning ◽  
Authoring Tools ◽  
Learning Content ◽  
Learning Content Management ◽  
Design Theories ◽  
Enhanced Learning ◽  
Content Management Systems

This chapter looks at the potential to exploit existing technology enhanced learning (TEL) authoring tools to provide customised learning solutions that address both businesses’ needs and employees learning requirements. It examines the feasibility of integrating training needs analysis into existing authoring tools to automate customisation. The chapter outlines a framework for such using best practices in the technology enhanced learning field such as sound instructional design theories, standard compliant metadata sets, and LO granularity while exploiting well established TEL authoring models. The chapter also highlights how this framework was implemented in practice in the form of an electronic tool that ties closely with existing learning content management systems.

Edu-ACoCM

2019 ◽  
Vol 9 (1) ◽  
pp. 16-40
Author(s):  
Maitri Maulik Jhaveri ◽  
Jyoti Pareek
Keyword(s):  
Content Management ◽  
Management Systems ◽  
Topic Extraction ◽  
Rule Based ◽  
Classification Approach ◽  
Automatic Feature Extraction ◽  
Learning Content ◽  
Learning Content Management ◽  
Learning Paths ◽  
Content Management Systems

Online learning repositories are the heart of learning content management systems. This article proposes a model that utilizes the educational content of learning repositories, to create and display multiple learning paths to the students. When a student specifies a topic to study, the model creates the learning paths in form of a tree, with student specified learning concepts as the root node and its co-existing concepts as the child nodes. The model also proposes to automatically extract three co-existing concepts: prerequisites, subsequent topics and features. Use of pattern-based mining and a rule-based classification approach is proposed for the extraction of co-existing concepts. Automatically extracted results are checked for meaningfulness and usefulness against expert generated results. Evaluation of the authors' model on various learning materials shows the appropriate generation of learning paths depicting the co-exiting concepts. The average F1 score obtained for automatic prerequisite extraction is 78%, automatic subsequent topic extraction is 83% and automatic feature extraction is 88%.

A Data Mining Service to Assist Instructors Involved in Virtual Education

2011 ◽  
pp. 222-243
Author(s):  
Marta E. Zorrilla ◽  
Diego García
Keyword(s):  
Data Mining ◽  
Data File ◽  
Content Management ◽  
On Demand ◽  
Virtual Courses ◽  
Learning Content ◽  
Learning Content Management ◽  
External Software ◽  
Behavior Profiles ◽  
Content Management Systems

In this chapter we present a BI application delivered as a service on-demand. In particular, it is a data mining service that aims to help instructors involved in distance education to discover their students’ behavior profiles and models about how they navigate and work in their virtual courses offered in Learning Content Management Systems such as Blackboard or Moodle. The main characteristic is that the users do not require data mining knowledge to use the service; they only have to send a data file according to one of the templates provided by the system and request the results. The service carries out the KDD process itself. Furthermore, the service provides an interface based on Web services, which can be called by external software. In short, the chapter talks about the necessity of a service with these characteristics and includes the description of its architecture and its method of operation as well as a discussion about some of the patterns it offers and how these provide instructors valuable knowledge to make decisions.

A Data Mining Service to Assist Instructors Involved in Virtual Education

Data Mining ◽  
2013 ◽  
pp. 1291-1311
Author(s):  
Marta E. Zorrilla ◽  
Diego García
Keyword(s):  
Data Mining ◽  
Data File ◽  
Content Management ◽  
On Demand ◽  
Virtual Courses ◽  
Learning Content ◽  
Learning Content Management ◽  
External Software ◽  
Behavior Profiles ◽  
Content Management Systems

In this chapter we present a BI application delivered as a service on-demand. In particular, it is a data mining service that aims to help instructors involved in distance education to discover their students’ behavior profiles and models about how they navigate and work in their virtual courses offered in Learning Content Management Systems such as Blackboard or Moodle. The main characteristic is that the users do not require data mining knowledge to use the service; they only have to send a data file according to one of the templates provided by the system and request the results. The service carries out the KDD process itself. Furthermore, the service provides an interface based on Web services, which can be called by external software. In short, the chapter talks about the necessity of a service with these characteristics and includes the description of its architecture and its method of operation as well as a discussion about some of the patterns it offers and how these provide instructors valuable knowledge to make decisions.

scholarly journals ICT Usage and E-Courses Development by Faculty Staff in Healthcare Majors at Medical University – Plovdiv

TEM Journal ◽  
2020 ◽  
pp. 731-739
Author(s):  
Angelina Kirkova-Bogdanova ◽  
Daniela Taneva
Keyword(s):  
Academic Staff ◽  
Content Management ◽  
Management Systems ◽  
Barriers To Learning ◽  
Learning Content ◽  
Learning Content Management ◽  
E Learning ◽  
Need For Support ◽  
Medical University ◽  
Content Management Systems

The aims of this study were to investigate the extent and benefits of ICT usage; barriers to learning content management systems (LCMS) deployment; perception and attitude to e-learning of the academic staff in the healthcare majors at the Medical University – Plovdiv. The results indicated that the educators use technologies extensively, they are experienced with computers but this is not a predisposition for teaching in the LCMS. Staff demonstrates acceptance of e-learning and critical attitude to its implementation, but the activity in the LCMS is low. Leading barriers in e-course creation are the heavy workload and the need for support in creating interactive learning content. A training course framework is proposed.

Sign in / Sign up

Export Citation Format

Share Document