Evaluation of Learning, Performance, and Productivity

1977 ◽  
Vol 5 (4) ◽  
pp. 341-353
Author(s):  
P. D. Maher
Keyword(s):  
System Design ◽  
Learning Systems ◽  
Learning System ◽  
Learning Performance ◽  
Survey Questionnaire ◽  
Applied Learning ◽  
Certificate Program ◽  
Evaluation Of Learning

This presentation informally explores some of the requirements for understanding evaluation goals and techniques in designing learning systems. It attempts to further clarify what is meant by the term or title of “applied learning technologist.” The theme is approached in layman's terms, concentrating on the need for validating both the “learning” requirements and the corresponding “learning system” design. Suggested contents of a curricula for an “applied learning technologist” certificate program are discussed. The results of a survey questionnaire distributed at the presentation are summarized at the end of the paper (see Appendix).

The Management of Learning Systems

1977 ◽  
Vol 5 (3) ◽  
pp. 245-254 ◽  
Author(s):  
George P. Doherty
Keyword(s):  
Graduate Program ◽  
Degree Program ◽  
Learning Systems ◽  
Learning System ◽  
Graduate Degree ◽  
Applied Learning ◽  
Good Management ◽  
Graduate Degree Program

The rationale and need for including a component on the management of learning systems in a graduate program is discussed. The major components associated with managing learning systems are described to provide ideas for the content of a graduate degree program. Since every applied learning system is made of many components which interact to produce specific results, good management is essential if the components are to interact synergistically to achieve optimum outcomes.

scholarly journals Benefits of Adaptive Learning Transfer from Typing-Based Learning to Speech-Based Learning

2021 ◽  
Author(s):  
Thomas Wilschut ◽  
Florian Sense ◽  
Maarten van der Velde ◽  
Zafeirios Fountas ◽  
Sarah Maass ◽  
...  
Keyword(s):  
Language Learning ◽  
Real Time ◽  
Word Learning ◽  
Adaptive Learning ◽  
Learning Algorithm ◽  
Foreign Language Learning ◽  
Learning Systems ◽  
Learning System ◽  
Learning Performance ◽  
Adaptive Learning Systems

Memorising vocabulary is an important aspect of formal foreign-language learning. Advances in cognitive psychology have led to the development of adaptive learning systems that make vocabulary learning more efficient. One way these computer-based systems optimize learning is by measuring learning performance in real time to create optimal repetition schedules for individual learners. While such adaptive learning systems have been successfully applied to word learning using keyboard-based input, they have thus far seen little application in spoken word learning. Here we present a system for adaptive, speech-based word learning using an adaptive model that was developed for and tested with typing-based word learning. We show that typing- and speech-based learning result in similar behavioral patterns that can be used to reliably estimate individual memory processes, and we extend earlier findings demonstrating that a response-time based adaptive learning system outperforms an accuracy-based, Leitner flashcard learning algorithm. In short, we show that adaptive learning benefits transfer from typing-based learning, to speech based learning. Our work provides a basis for the development of language learning applications that use real-time pronunciation assessment software to score the accuracy of the learner's pronunciations. The development of adaptive, speech-based learning applications is important for two reasons. First, by focusing on speech, the model can be applied for individuals whose typing skills are insufficient---as is demonstrated by the successful application of the model in an elderly participant population. Second, speech-based learning models are educationally relevant because they focus on what may be the most important aspect of language learning: to practice speech.

The Role of Interactive and Synchronized Multimedia Content in E-Learning

2011 ◽  
pp. 232-250
Author(s):  
Dongsong Zhang ◽  
Lina Zhou
Keyword(s):  
Empirical Study ◽  
Knowledge Construction ◽  
Learning Systems ◽  
Learning System ◽  
Learning Performance ◽  
Multimedia Content ◽  
Significant Evidence ◽  
Learning Content ◽  
E Learning

Multimedia-based e-learning systems have become increasingly available. Many of them, however, do not provide sufficient interactivity to learners. E-learners have little control over learning content and process to meet their individual needs. Therefore, the challenges include how to integrate instructional material in different media, and how to provide flexible process control in an e-learning environment to enable personalized knowledge construction and improve learning effectiveness. We propose an e-learning system with interactive multimedia that can help learners better understand learning content and achieve comparable learning performance to that of classroom learning. The results from an empirical study provide significant evidence to support our proposition. The chapter also discusses several important issues towards building effective and sharable multimedia-based e-learning systems.

scholarly journals Development of a Game-Based e-Learning System with Augmented Reality for Improving Students’ Learning Performance

2020 ◽  
Vol 2 (1) ◽  
pp. 1-10
Author(s):  
Shu-Hung Yang ◽  
Yu-Ying Wang ◽  
Ah-Fur Lai ◽  
Yi-Nan Lin ◽  
Gwo-Jen Chiou ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Extracurricular Activities ◽  
School Children ◽  
Learning Systems ◽  
Learning System ◽  
Learning Performance ◽  
Traditional Learning ◽  
Game Engine ◽  
Teaching Activities ◽  
E Learning

Currently, the school children usually spend a lot of time on the games in their recreational activities and some of them are even addicted to the games. Compared with other extracurricular activities, the e-Learning system reflects the fact that school children are very interested in the games. As a result, educators have lately craved to develop effective teaching activities that allow the school children to learn some subjects and to play the games simultaneously.  Therefore, this study is based on an e-Learning system which combines the serious game by Unity3D Game Engine with augmented reality (AR). Students are able to acquire their knowledge and to foster logical skills via this game-based e-Learning system.  According to its efficacy and utilities, this study has assessed and compared the game-based e-Learning system with the traditional learning and other e-Learning systems. The experimental results have indicated that the proposed game-based e-Learning system can outperform other existing systems.

Tensor relational algebra for distributed machine learning system design

2021 ◽  
Vol 14 (8) ◽  
pp. 1338-1350
Author(s):  
Binhang Yuan ◽  
Dimitrije Jankov ◽  
Jia Zou ◽  
Yuxin Tang ◽  
Daniel Bourgeois ◽  
...  
Keyword(s):  
Machine Learning ◽  
Empirical Study ◽  
System Design ◽  
High Efficiency ◽  
Learning Systems ◽  
Learning System ◽  
Relational Algebra ◽  
Activation Functions ◽  
Distributed Environment ◽  
Distributed Machine Learning

We consider the question: what is the abstraction that should be implemented by the computational engine of a machine learning system? Current machine learning systems typically push whole tensors through a series of compute kernels such as matrix multiplications or activation functions, where each kernel runs on an AI accelerator (ASIC) such as a GPU. This implementation abstraction provides little built-in support for ML systems to scale past a single machine, or for handling large models with matrices or tensors that do not easily fit into the RAM of an ASIC. In this paper, we present an alternative implementation abstraction called the tensor relational algebra (TRA). The TRA is a set-based algebra based on the relational algebra. Expressions in the TRA operate over binary tensor relations, where keys are multi-dimensional arrays and values are tensors. The TRA is easily executed with high efficiency in a parallel or distributed environment, and amenable to automatic optimization. Our empirical study shows that the optimized TRA-based back-end can significantly outperform alternatives for running ML workflows in distributed clusters.

Factors Associated with students’ Intention to use E-Learning System: A Study from Public Universities of Lahore

2021 ◽  
Vol 9 (2) ◽  
pp. 167-173
Author(s):  
Shagufta Shaheen ◽  
Mubasher Muhammad Kamran ◽  
Saira Naeem ◽  
Tahir Mahmood
Keyword(s):  
Undergraduate Students ◽  
Public Universities ◽  
Positive Impact ◽  
Cross Sectional Study ◽  
Learning Systems ◽  
Learning System ◽  
Policy Implications ◽  
Intention To Use ◽  
Cross Sectional ◽  
E Learning

The study's primary purpose is to explore the factors affecting the students' intention to use e-learning systems in the COVID pandemic. The model of the “Unified theory of acceptance and use of technology” (UTAUT) was used as a theoretical underpinning. The Independent variables include “performance expectancy, effort expectancy, social influence, facilitating condition,” and the dependent variable is the intention to use e-learning systems. The quantitative data were collected from the postgraduate and undergraduate students of the public universities of Lahore. A total of n=411 students were approached, out of which the responses of only 399 were considered valid and were used for Multiple linear regression through SPSS 25. It was a cross-sectional study. It was found that almost all constructs of the model have a significant positive impact on intention to use e-learning systems.  The study's main contribution is exposing the factors that affect the acceptance and use of e-learning systems. This study has several policy implications for policy experts of higher education”.

scholarly journals Building Learning System for Content Knowledge and Social Knowledge

2018 ◽  
Vol 13 (01) ◽  
pp. 4
Author(s):  
S.M.F.D Syed Mustapha
Keyword(s):  
Content Knowledge ◽  
Intelligent Tutoring System ◽  
Individual Learning ◽  
Learning Systems ◽  
Learning System ◽  
Social Knowledge ◽  
Computer Based Training ◽  
Web 3.0 ◽  
Knowledge Models ◽  
Computer Aided

In the late 50’s or early 60’s, there were huge interests towards building learning systems for individual learning and they are called with various names such as Intelligent Tutoring System, Microworld, Computer Based Training, Computer Aided System, Intelligent Computer Aided Instruction and others. They are made to be different with regard to the technological approaches and the learning pedagogies, knowledge models and student models. Over the years, the interest of building learning systems has migrated from individual learning on content knowledge to community learning as the result of the recent Web 2.0 and Web 3.0 sociotechnological wave. The paper describes the work that was done to develop the learning system in both situations – content knowledge and social knowledge where the experiences mainly in capturing the knowledge and representing them are different

scholarly journals Trust between Humans and Learning Machines: Developing the Gray Box

2017 ◽  
Vol 139 (06) ◽  
pp. S9-S13 ◽  
Author(s):  
James C. Christensen ◽  
Joseph B. Lyons
Keyword(s):  
Situation Awareness ◽  
Task Allocation ◽  
Intelligent Agent ◽  
Semantic Space ◽  
Learning Systems ◽  
Learning System ◽  
Sufficient Information ◽  
Learning Technology ◽  
Learning Machines ◽  
Potential Impact

This article explores the notion of the ‘Gray Box’ to symbolize the idea of providing sufficient information about the learning technology to establish trust. The term system is used throughout this article to represent an intelligent agent, robot, or other form of automation that possesses both decision initiative and authority to act. The article also discusses a proposed and tested Situation Awareness-based Agent Transparency (SAT) model, which posits that users need to understand the system’s perception, comprehension, and projection of a situation. One of the key challenges is that a learning system may adopt behavior that is difficult to understand and challenging to condense to traditional if-then statements. Without a shared semantic space, the system will have little basis for communicating with the human. One of the key recommendations of this article is that there is a need to provide learning systems with transparency as to the state of the human operator, including their momentary capabilities and potential impact of changes in task allocation and teaming approach.

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