Developing Technical Training: Structured Approach for Developing Classroom and Computer-Based Instructional Materials (2nd Edition)

Clark, Ruth Colvin; Shadden, Marie

doi:10.1002/pfi.4140400409

Cited by 32 publications

(51 citation statements)

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“…One of the fundamental hypotheses of ACT-R is that knowledge and skills are acquired and strengthened through actual practice [Anderson 1993]. Experiments with cognitive tutors have shown that students who practice skills that they have just learned perform better than students who do not [Aleven and Koedinger 2002;Eberts 1997;Schmidt and 6 · P. Kumaraguru et al [Clark 1989]. A procedure is a series of clearly defined steps which results in the achievement of a given task (e.g.…”

Section: Instructional Design Principlesmentioning

confidence: 99%

Teaching Johnny not to fall for phish

Kumaraguru

Sheng

Acquisti

et al. 2010

ACM Trans. Internet Technol.

278

226

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Phishing attacks, in which criminals lure Internet users to websites that spoof legitimate websites, are occurring with increasing frequency and are causing considerable harm to victims. While a great deal of effort has been devoted to solving the phishing problem by prevention and detection of phishing emails and phishing websites, little research has been done in the area of training users to recognize those attacks. Our research focuses on educating users about phishing and helping them make better trust decisions. We identified a number of challenges for end-user security education in general and anti-phishing education in particular: users are not motivated to learn about security; for most users, security is a secondary task; it is difficult to teach people to identify security threats without also increasing their tendency to misjudge non-threats as threats. Keeping these challenges in mind, we developed an email-based anti-phishing education system called "PhishGuru" and an online game called "Anti-Phishing Phil" that teaches users how to use cues in URLs to avoid falling for phishing attacks. We applied learning science instructional principles in the design of PhishGuru and Anti-Phishing Phil. In this paper we present the results of PhishGuru and Anti-Phishing Phil user studies that demonstrate the effectiveness of these tools. Our results suggest that, while automated detection systems should be used as the first line of defense against phishing attacks, user education offers a complementary approach to help people better recognize fraudulent emails and websites.

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Section: Instructional Design Principlesmentioning

confidence: 99%

Teaching Johnny not to fall for phish

Kumaraguru

Sheng

Acquisti

et al. 2010

ACM Trans. Internet Technol.

278

226

View full text Add to dashboard Cite

show abstract

“…Extensive research has been conducted all over the world to examine the influence of digital resources on learning. The results of these studies, confirmatory and/or contradictory, seem to agree that the learning process accelerates and stimulates the way the subject matter is presented via a medium rather than the type of medium or the medium itself (20). Research has been conducted on technological infrastructure, hardware, and instructional material for several decades.…”

Section: Introductionmentioning

confidence: 67%

Prediction of Achievement based on Different Dimensions of E-learning Materials in University of Mysore, India

Rahmani

Sheela

2017

Interdiscip J Virtual Learn Med Sci

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Background: Educational systems have adopted e-learning in high quantity all over the world and they are currently concerned about the quality of instruction. Different factors including pedagogical factors, technical factors, content issues, ease of use of elearning systems, and computer knowledge of the users constitute the quality dimensions. The present study examines the degree of which each dimension affects the achievement in e-learning settings. Methods: The present semi-experimental research was conducted in teacher education colleges affiliated to University of Mysore, India, in 2015 -2016. Pretest on educational psychology (EP) was administered to 72 students selected through purposive sampling technique. The students were treated through e-learning by the researcher for 16 sessions. EP posttest and E-learning dimensions evaluation questionnaire (ELDEQ) were administered at the end of the intervention. ELDEQ contained 58 questions on the quality of e-learning dimensions and it was constructed based on the evidence from content analysis. Face validity and content validity of the instrument were established through 13 experts in the field of e-content. Confirmatory Factor Analysis (CFA) was adopted to establish construct validity. Cronbach's alpha above 0.7 indicated the reasonable reliability of the instrument. SPSS 22 and multiple regression were utilized to analyze the data. Results:The results indicated a difference between the effects of various dimensions including content dimension (P = 0.001), technical dimension (P = 0.03), pedagogical dimension (P = 0.02), computer knowledge of the users (P = 0.47), and ease of use of elearning systems (P = 0.17) on achievement. Conclusions: Based on the results of the study, content dimension is the first and foremost predictor of learning. Pedagogical and technical dimensions were found to be the second and the third significant predictors of achievement, respectively.

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“…The component display theory provides the foundation for Clark's performance matrix [9]. Clark's performance matrix, along with Merrill's component display theory, can help designers classify instructional outcomes and are developed in some content models, such as the Cisco [3] and Learnativity [44] models.…”

Section: The Component Display Theorymentioning

confidence: 99%

“…Learning objects are a collection The Learnativity model incorporates concepts found in structured writing [18] and the vocabulary of the LOM learning resource type [12]. Themes found in Clark's writings [9] and in a corporate training white paper published by Cisco Systems [3] are developed in the Learnativity model [32]. The model has gained considerable acceptance in both training and education communities.…”

Section: Learnativity Content Modelmentioning

confidence: 99%

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ALOCOM: a generic content model for learning objects

Verbert

Duval

2008

Int J Digit Libr

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e-Learning organizations are focusing heavily on learning content reusability. The ultimate objective is a learning object economy characterized by searchable digital libraries of reusable learning objects that can be exchanged and reused across various learning systems. To enable such approach, basic questions of learning content interoperability need to be addressed. This paper investigates the interoperation of learning content defined according to different specifications. A number of content models are reviewed that define learning objects and their components. On the basis of a comparative analysis, the content models are mapped to a generic model for learning objects to address interoperability questions and to enable share and reuse on a global scale.

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Developing Technical Training: Structured Approach for Developing Classroom and Computer-Based Instructional Materials (2nd Edition)

Cited by 32 publications

References 0 publications

Teaching Johnny not to fall for phish

Teaching Johnny not to fall for phish

Prediction of Achievement based on Different Dimensions of E-learning Materials in University of Mysore, India

ALOCOM: a generic content model for learning objects

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