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Journal articles on the topic 'Electronic Performance Support System'

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Published: 4 June 2021
Last updated: 19 February 2022

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1

Fischer, Olivier, and Richard Horn. "Electronic performance support systems." Communications of the ACM 40, no. 7 (July 1997): 31–32. http://dx.doi.org/10.1145/256175.256180.

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2

Williams, Kent E., and Timothy G. Kotnour. "An electronic performance support system for organizational learning." Computers & Industrial Engineering 25, no. 1-4 (September 1993): 93–97. http://dx.doi.org/10.1016/0360-8352(93)90229-q.

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3

Barker, Philip, and Ashok Banerji. "Designing Electronic Performance Support Systems." Innovations in Education and Training International 32, no. 1 (February 1995): 4–12. http://dx.doi.org/10.1080/1355800950320102.

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4

Miller, Bill. "A system design model for an electronic performance support system." Performance + Instruction 34, no. 7 (August 1995): 24–26. http://dx.doi.org/10.1002/pfi.4170340708.

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5

Sumuer, Evren, and Soner Yildirim. "Exploring User Acceptance of an Electronic Performance Support System." Performance Improvement Quarterly 27, no. 4 (January 2015): 29–48. http://dx.doi.org/10.1002/piq.21178.

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6

Folmer, Elvira, Nienke Nieveen, and Kim Schildkamp. "An electronic performance support system to support teachers in (re-)designing curricula." International Journal of Learning Technology 6, no. 2 (2011): 183. http://dx.doi.org/10.1504/ijlt.2011.042648.

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7

Laffey, James. "Dynamism in Electronic Performance Support Systems." Performance Improvement Quarterly 8, no. 1 (October 22, 2008): 31–46. http://dx.doi.org/10.1111/j.1937-8327.1995.tb00660.x.

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8

Desmarais, Michael C., Richard Leclair, Jean-Yves Fiset, and Hichem Talbi. "Cost-justifying electronic performance support systems." Communications of the ACM 40, no. 7 (July 1997): 39–48. http://dx.doi.org/10.1145/256175.256183.

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9

Sezer, Baris, and Nurettin Simsek. "Designing an electronic performance support system for technology-rich environments." Behaviour & Information Technology 37, no. 6 (May 5, 2018): 596–606. http://dx.doi.org/10.1080/0144929x.2018.1469669.

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Altalib, Hasan. "ROI calculations for electronic performance support systems." Performance Improvement 41, no. 10 (November 2002): 12–22. http://dx.doi.org/10.1002/pfi.4140411005.

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Choi, Jeong Im. "The definition and des ign principles of Electronic Performance Support System." Journal of Educational Technology 13, no. 2 (December 30, 1997): 361–77. http://dx.doi.org/10.17232/kset.13.2.361.

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12

Putra, Benaya, Sulton Sulton, and Yerry Soepriyanto. "Pengembangan Screencast sebagai Electronic Performance Support System dalam Pemanfaatan Sipejar UM." JKTP: Jurnal Kajian Teknologi Pendidikan 2, no. 4 (November 30, 2019): 252–60. http://dx.doi.org/10.17977/um038v2i42019p252.

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13

Milheim, William. "Instructional Design Issues for Electronic Performance Support Systems." British Journal of Educational Technology 28, no. 2 (April 1997): 103–10. http://dx.doi.org/10.1111/1467-8535.00014.

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14

Nguyen, Frank, James D. Klein, and Howard Sullivan. "A Comparative Study of Electronic Performance Support Systems." Performance Improvement Quarterly 18, no. 4 (October 22, 2008): 71–86. http://dx.doi.org/10.1111/j.1937-8327.2005.tb00351.x.

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15

Schaik, Paul Van, Robert Pearson, and Philip Barker. "Designing Electronic Performance Support Systems to Facilitate Learning." Innovations in Education and Teaching International 39, no. 4 (January 2002): 289–306. http://dx.doi.org/10.1080/13558000210161043.

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16

Raybould, Barry. "Solving human performance problems with computers a case study: Building an electronic performance support system." Performance + Instruction 29, no. 10 (November 1990): 4–14. http://dx.doi.org/10.1002/pfi.4160291004.

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17

Ranade, Eeshan. "Electronic Control System for Steer by Wire." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4161–66. http://dx.doi.org/10.22214/ijraset.2021.35968.

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Automobile industry’s focus is on efficiency, safety and performance has resulted in the rapid introduction of electronics in vehicle safety systems and engine management. Mechanical and Hydraulic systems are now gradually being replaced by electronic controllers to achieve the objectives of optimizing power consumption, improving driver convenience, and maximizing driver safety resulting in an overall improved performance and experience. Vehicle steering systems have transitioned from mechanical to hydraulic power to an electric power assisted steering system and now to the state of the art, Steer by Wire (SbW) system. Traditional mechanical systems included a steering wheel, column, gear, rack and pinion and did not support any power steering. The next generation hydraulic systems were more stable, safer and required comparatively lesser effort. Electric or DC motors drove the Electric Power System addressing the drawbacks of the hydraulic systems especially those related to environment and acoustics with the added advantage of a compact structure and power-on-demand engine performance. By-wire steering technologies was originally introduced in the Concord aircraft in 1970s. The SbW is a steering system with no steering column. The mechanical interface between the steering wheel and the wheels is replaced with by-wire electrical connection/electronic actuators. SbW system has significant advantages in terms of driving safety due to the availability of the steering command in electronic form and the removal of the steering shaft, cruising comfort with driving manoeuvring due to no space constraint and favourable to the environment with the non-usage of hydraulic oils.
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18

Davis, David. "Electronic Performance Support Systems in Elementary and Secondary Schools." Innovations in Education and Training International 32, no. 1 (February 1995): 31–34. http://dx.doi.org/10.1080/1355800950320105.

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19

Bastiaens, Theo J. "Assessing an electronic performance support system for the analysis of jobs and tasks." International Journal of Training and Development 3, no. 1 (March 1999): 54–61. http://dx.doi.org/10.1111/1468-2419.00064.

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20

Yakin, Ilker, and Soner Yildirim. "Evaluating an electronic performance support system for crime scene investigation units in Turkey." Information Development 32, no. 4 (July 9, 2016): 1068–84. http://dx.doi.org/10.1177/0266666915587129.

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21

Witarsyah, Deden, Mohd Farhan Md Fudzee, Mohamad Aizi Salamat, Iwan Tri Riyadi Yanto, and Jemal Abawajy. "Soft Set Theory Based Decision Support System for Mining Electronic Government Dataset." International Journal of Data Warehousing and Mining 16, no. 1 (January 2020): 39–62. http://dx.doi.org/10.4018/ijdwm.2020010103.

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Electronic government (e-gov) is applied to support performance and create more efficient and effective public services. Grouping data in soft-set theory can be considered as a decision-making technique for determining the maturity level of e-government use. So far, the uncertainty of the data obtained through the questionnaire has not been maximally used as an appropriate reference for the government in determining the direction of future e-gov development policy. This study presents the maximum attribute relative (MAR) based on soft set theory to classify attribute options. The results show that facilitation conditions (FC) are the highest variable in influencing people to use e-government, followed by performance expectancy (PE) and system quality (SQ). The results provide useful information for decision makers to make policies about their citizens and potentially provide recommendations on how to design and develop e-government systems in improving public services.
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22

Moore, Joi L., and Michael A. Orey. "The Implementation of an Electronic Performance Support System for Teachers: An Examination of Usage, Performance, and Attitudes." Performance Improvement Quarterly 14, no. 1 (October 22, 2008): 26–56. http://dx.doi.org/10.1111/j.1937-8327.2001.tb00200.x.

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23

Chang *, Chi‐Cheng. "The relationship between the performance and the perceived benefits of using an electronic performance support system (EPSS)." Innovations in Education and Teaching International 41, no. 3 (August 2004): 343–64. http://dx.doi.org/10.1080/14703290410001733249.

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24

Ma, Yuxin, and Stephen W. Harmon. "Integrating Knowledge Management Systems, Electronic Performance Support Systems, and Learning Technologies." Performance Improvement Quarterly 19, no. 3 (October 22, 2008): 107–20. http://dx.doi.org/10.1111/j.1937-8327.2006.tb00380.x.

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25

Gery, Gloria. "Preface to the Special Issue on Electronic Performance Support Systems." Performance Improvement Quarterly 8, no. 1 (October 22, 2008): 3–6. http://dx.doi.org/10.1111/j.1937-8327.1995.tb00657.x.

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26

Cagiltay, Kursat. "Scaffolding strategies in electronic performance support systems: types and challenges." Innovations in Education and Teaching International 43, no. 1 (February 2006): 93–103. http://dx.doi.org/10.1080/14703290500467673.

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27

Barker, Philip, Paul van Schaik, and Oladeji Famakinwa. "Building electronic performance support systems for first‐year university students." Innovations in Education and Teaching International 44, no. 3 (August 2007): 243–55. http://dx.doi.org/10.1080/14703290701486530.

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28

Ugur-Erdogmus, Feray, and Kursat Cagiltay. "Making novice instructional designers expert: Design and development of an electronic performance support system." Innovations in Education and Teaching International 56, no. 4 (March 23, 2018): 470–80. http://dx.doi.org/10.1080/14703297.2018.1453853.

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29

Qu, Feng Zhen, and Bao Cheng Lu. "Comparative Study of the Auto Electronic Control System." Applied Mechanics and Materials 539 (July 2014): 587–91. http://dx.doi.org/10.4028/www.scientific.net/amm.539.587.

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Based on mathematical principle of function interpolation we design dominant and recessive auto electronic control system. In order to compare the performance of the two systems, we design a control experiment of automobile electronic signals for these two systems. The system adopts the CAN bus control, the wheel speed and door signal use the 0001-0100 signal channel to control, oil pressure and fault signal use the 0100-1111 signal channel to control. From the testing results of two systems, the dominant auto electronic control system occupies 8 channels, which is far from the theoretical value; and the recessive control occupies only 2 channels, which is accord with the theoretical value. It provides the technical support for the design of automotive electronic control system
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30

Saleem, Farrukh, Zahid Ullah, Bahjat Fakieh, and Faris Kateb. "Intelligent Decision Support System for Predicting Student’s E-Learning Performance Using Ensemble Machine Learning." Mathematics 9, no. 17 (August 27, 2021): 2078. http://dx.doi.org/10.3390/math9172078.

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Electronic learning management systems provide live environments for students and faculty members to connect with their institutional online portals and perform educational activities virtually. Although modern technologies proactively support these online sessions, students’ active participation remains a challenge that has been discussed in previous research. Additionally, one concern for both parents and teachers is how to accurately measure student performance using different attributes collected during online sessions. Therefore, the research idea undertaken in this study is to understand and predict the performance of the students based on features extracted from electronic learning management systems. The dataset chosen in this study belongs to one of the learning management systems providing a number of features predicting student’s performance. The integrated machine learning model proposed in this research can be useful to make proactive and intelligent decisions according to student performance evaluated through the electronic system’s data. The proposed model consists of five traditional machine learning algorithms, which are further enhanced by applying four ensemble techniques: bagging, boosting, stacking, and voting. The overall F1 scores of the single models are as follows: DT (0.675), RF (0.777), GBT (0.714), NB (0.654), and KNN (0.664). The model performance has shown remarkable improvement using ensemble approaches. The stacking model by combining all five classifiers has outperformed and recorded the highest F1 score (0.8195) among other ensemble methods. The integration of the ML models has improved the prediction ratio and performed better than all other ensemble approaches. The proposed model can be useful for predicting student performance and helping educators to make informed decisions by proactively notifying the students.
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31

Juang, Yih-Ruey, Tzu-Chien Liu, and Tak-Wai Chan. "Web-based performance support system for school-based curriculum development: SBCDSS." Computer Science and Information Systems 2, no. 2 (2005): 37–64. http://dx.doi.org/10.2298/csis0502037j.

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School-based curricula are seen as the important strategy to facilitate educational reforms and are spread in many countries, especially in Asia. However, the efficiency of developing and implementing school-based curricula in most schools are very low because the tasks those need to be dealt with are very complex and difficult. How to develop and apply the electronic performance support system (EPSS) to simplify the complexity and to improve the efficiency of school" based curriculum development and implementation becomes the important research and practical issue. In our prior work, a web-based computer-assisted instructional planning system IPASS, was designed to provide a set of tools for individual teachers efficiently designing instructional plans. However, the system was dedicated for the design phase of curriculum development and did not support for all participants in different levels of school-based curriculum development working on curriculum analysis, design, implementation and evaluation. This study designs and develops a novel web-based performance support system SBCDSS, to assist the whole process of school-based curriculum development and implementation. The proposed system has been adopted in an elementary school in Taiwan and has received useful feedback regarding the usability and performance support for SBCD. Evaluation results and possible future work are discussed herein.
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32

Layton, Charles F., Michael J. Christodoulou, Joseph T. Jackson, and Jonathan L. Turner. "Lessons Learned in the Development of Mobile Electronic Performance Support Systems." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 39, no. 4 (October 1995): 268–72. http://dx.doi.org/10.1177/154193129503900410.

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There are a number of interacting constraints that affect the development of mobile electronic performance support systems (Gery, 1991). For example, users frequently want the resources of a desktop computer in a palm-sized box. Hardware technology, however, dictates that the greater the resources, the larger the device. Mobile electronic performance support systems are frequently initiated as a means to ‘automate’ manual processes. However, such processes must be redesigned to match the capabilities and requirements of mobile computing platforms. As a final example, the desktop conventions of “new, open, and save” used when working with documents are not necessarily the best conventions for mobile applications. This paper identifies many of the constraints involved in developing mobile computing applications and discusses them in the context of applications.
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33

Mitchem, Katherine J., Gail Fitzgerald, Kevin Miller, and Candice Hollingsead. "Using Electronic Performance Support Systems to Improve Academic Performance of Secondary Students with Disabilities." Journal of Special Education Technology 28, no. 3 (September 2013): 1–20. http://dx.doi.org/10.1177/016264341302800301.

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34

Mileva, Nevena, and Ivan Stanchev. "From web-based instructional systems to browser-based electronic performance support systems." International Journal of Continuing Engineering Education and Lifelong Learning 10, no. 1/2/3/4 (2000): 286. http://dx.doi.org/10.1504/ijceell.2000.000371.

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35

Wang, Wei, Li Huang, Yuliang Zhu, Liupeng Jiang, Anoop Kumar Sahu, Atul Kumar Sahu, and Nitin Kumar Sahu. "Decision support system toward evaluation of resilient supplier." Kybernetes 49, no. 6 (November 23, 2019): 1741–65. http://dx.doi.org/10.1108/k-05-2019-0345.

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Purpose Supplier evaluation is a part of logistic management. In the present era, resilient supply chain performance (RSCP) assessment of the vendor enterprise is respected as a hot topic. The purpose of this paper is to enable the managers to map the performance in percentage system and also enabling managers for identifying the weak indices-metrics, which need to be improved up to ideal or standard level and strong indices-metrics. Design/methodology/approach The authors found two research gaps via a literature survey. The first research gap revealed that the performance of a resilient supplier is computed solely in terms of a fuzzy mathematical scale. The articles are not yet published, which could measure the RSCP in percentage. The second research gap argued about the mitigation of the multi-level hierarchical resilient vendor/supplier evaluation framework for materializing RSCP and identifying weak and strong performing indices-metrics. To compensate the both research gaps, the authors developed a novel fuzzy gain-loss evolutionary computational approach to assess the performance of a firm in percentage. Next, a revised ranking technique coupled with trapezoidal fuzzy set based fuzzy performance importance index is implemented on the framework to seek weak and strong indices-metrics. The performance loss of each metric using the ideal solution concept considering the attitude of decision makers is also revealed. Findings The authors found the RSC performance of supplier firm 74 per cent, whereas performance loss 26 per cent, while actual performance is compared with standard fuzzy performance index (SFPI). Performance loss 26 per cent can be compensated by improving the performance of weak indices-metrics. Originality/value The novelty of the paper is that the authors used the ideal solution concept to compute the SFPI and compare it with actual FPI for evaluating the gain and loss of resilient supplier firm in percentage and identify weak and strong indices so that managers can improve the performance of weak indices. The work possesses the significant for all organizations, as research work enables the managers to map and improve the RSC performance of any vendor firm in future. The presented work considers the case of an automobile parts supplier industry to validate the developed approach.
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36

Bastiaens, Theo J., Wim J. Nijhof, Jan N. Streumer, and Harmen J. Abma. "Working and learning with electronic performance support systems: an effectiveness study." Training for Quality 5, no. 1 (March 1997): 10–18. http://dx.doi.org/10.1108/09684879710156478.

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37

Chiero, Robin T. "Electronic Performance Support Systems: A New Opportunity to Enhance Teacher Effectiveness?" Action in Teacher Education 17, no. 4 (January 1996): 37–44. http://dx.doi.org/10.1080/01626620.1996.10463351.

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38

Bastiaens, Theo J., Wim J. Nijhof, Jan N. Streumer, and Harmen J. Abma. "Working and Learning with Electronic Performance Support Systems: An Effectiveness Study." International Journal of Training and Development 1, no. 1 (March 1997): 72–78. http://dx.doi.org/10.1111/1468-2419.00007.

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39

Clem, Jeffrey D. "The synthetic instructor: Implementation for Web-based electronic performance support systems." Performance Improvement 46, no. 8 (September 2007): 27–31. http://dx.doi.org/10.1002/pfi.155.

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40

Gal, Eran, and Rafi Nachmias. "The effect of users' attitudes on electronic performance support systems implementation." Performance Improvement 51, no. 5 (May 2012): 22–31. http://dx.doi.org/10.1002/pfi.21264.

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41

El-Nakla, Samir. "Case-Based Expert System to Support Electronics Design in Mechatronic System." Applied Mechanics and Materials 229-231 (November 2012): 2793–97. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.2793.

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Many current systems rely for their performance on achieving a balance between electronics, software and mechanical systems and the transfer of functionality between those domains. The design of such mechatronic systems therefore relies on the ability of the individual domain specialists to transfer knowledge about their domain within the overall design process. Enhancing the ability of non-specialists to understand the relationships between the various system elements and to communicate with the domain specialists will serve to enhance and support the design process. The paper therefore considers a tool based around the use of case-based expert system which is intended to provide such support by allowing a non-specialist to access information from a range of domains in a way which is easy to use and understand and which will establish and define the links between the various areas of technology.
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42

Darabi, Abbas, Melissa C. Mackal, and David W. Nelson. "Self-Regulated Learning of Performance Analysis as a Complex Cognitive Skill: Contributions of an Electronic Performance Support System (EPSS)." Journal of Educational Technology Systems 33, no. 1 (September 2004): 11–27. http://dx.doi.org/10.2190/upmk-vr6m-0adr-ca5u.

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43

Nandi, Debkumar, Abu Taher, Rafique Ul Islam, Samarjeet Siwal, Meenakshi Choudhary, and Kaushik Mallick. "Carbon nitride supported copper nanoparticles: light-induced electronic effect of the support for triazole synthesis." Royal Society Open Science 3, no. 11 (November 2016): 160580. http://dx.doi.org/10.1098/rsos.160580.

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The composite framework of graphitic carbon nitride ( g CN) supported copper nanoparticle can act as a high-performance photoreactor for the synthesis of 1,2,3-triazole derivatives under light irradiation in the absence of alkaline condition. The photoactivity of g CN originates from an electron transition from the valence band to the conduction band, in the presence of photon energy, and the hot electron acts as a scavenger of the terminal proton of the alkyne molecule to facilitate the formation of copper acetanilide complex. In this study, we have performed the experiment under a different photonic environment, including dark condition, and in the presence and absence of base. A comparative study was also executed using Cu-TiO 2 system, as a reference material, in the support of our proposed mechanism. The recycling performance and the photocorrosion effect of the catalyst have also been reported in this study.
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44

MERZ, MICHAEL, FRANK GRIFFEL, TUAN TU, STEFAN MÜLLER-WILKEN, HARALD WEINREICH, MARKO BOGER, and WINFRIED LAMERSDORF. "SUPPORTING ELECTRONIC COMMERCE TRANSACTIONS WITH CONTRACTING SERVICES." International Journal of Cooperative Information Systems 07, no. 04 (December 1998): 249–74. http://dx.doi.org/10.1142/s021884309800012x.

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Based on the specific characteristics and requirements for an adequate electronic commerce system support, this article gives an overview of the respective distributed systems technologies which are available for open and heterogeneous electronic commerce applications. Abstracting from basic communication mechanisms such as (transactionally secure) remote procedure calls and remote database access mechanisms, this includes service trading and brokerage functions as well as security aspects including such as notary and non-repudiation functions. Further important elements of a system infrastructure for electronic commerce applications are: Common middleware infrastructures, componentware techniques, distributed and mobile agent technologies etc. As electronic transactions enter the phase of performance, increasingly new and important functions are required. Among these are: Negotiation protocols to support both the settlement and fulfillment of electronic contracts as well as ad-hoc workflow management support for compound and distributed services in electronic commerce applications. In addition to an overview of the state of the art of the respective technology, the article briefly presents some related projects conducted by the authors jointly with international partners in order to realize some of the important new functions of a system infrastructure for open distributed electronic commerce applications.
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Alqahtani, Abdullah, Fahd Abdulsalam Alhaidari, Atta-ur-Rahman, Maqsood Mahmud, and Kiran Sultan. "Decision Support System Assisted E-Recruiting System." Journal of Computational and Theoretical Nanoscience 16, no. 2 (February 1, 2019): 335–40. http://dx.doi.org/10.1166/jctn.2019.7955.

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Individuals play a significant role to enhance and accelerate the performance of the organizations and hiring right employees, is indeed a challenging task. It is because many people show interest in the single job opening. HR in large organizations, recruits and explores such people by following proper recruitment process. This recruitment process has been proven to be lengthy, tidy and costly because of a substantial number of applicants. Recruitment of suitable individuals becomes more difficult for smaller organizations as they do not have HR department. Automation can improve the process though. By doing this, the process becomes shorter, easier, and cost effective. In that respect several automated recruiting systems have been proposed in the literature. The primary limitation of the existing recruitment systems is that it simply picks out those candidates who meet the (100%) skills set and turns down the rest of them yet if they are meeting the partial criteria. It intends that as these programs have been projected to pick only those who are gathering all the prerequisites. In fact, the recruitment system can select the candidates that are even meeting the near about or close requirements. It is because if a candidate does not meet (100%), then the candidate with the lesser requirement should be kept under consideration. There can be chances where a person meeting 9 out of 10 requirements could have proved to be the best choice, but because of the system we lose such candidates. The current research proposes a Fuzzy logic-based decision support system (DSS), to overcome the above-mentioned limitation. Abiding by the Fuzzy logic, the proposed system can view the partial skills of the applicants. The system has been validated by implementing the prototype. The outcomes depict a significant improvement to overcome the limitation of the existing recruitment systems.
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46

Perilla, Arcadio, José Luis Rueda Torres, Stelios Papadakis, Elyas Rakhshani, Mart van der Meijden, and Francisco Gonzalez-Longatt. "Power-Angle Modulation Controller to Support Transient Stability of Power Systems Dominated by Power Electronic Interfaced Wind Generation." Energies 13, no. 12 (June 19, 2020): 3178. http://dx.doi.org/10.3390/en13123178.

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During the last few years, electric power systems have undergone a widespread shift from conventional fossil-based generation toward renewable energy-based generation. Variable speed wind generators utilizing full-scale power electronics converters are becoming the preferred technology among other types of renewable-based generation, due to the high flexibility to implement different control functions that can support the stabilization of electrical power systems. This paper presents a fundamental study on the enhancement of transient stability in electrical power systems with increasing high share (i.e., above 50%) of power electronic interfaced generation. The wind generator type IV is taken as a representative form of power electronic interfaced generation, and the goal is to investigate how to mitigate the magnitude of the first swing while enhancing the damping of rotor angle oscillations triggered by major electrical disturbances. To perform such mitigation, this paper proposes a power-angle modulation (PAM) controller to adjust the post-fault active power response of the wind generator type IV, after a large disturbance occurs in the system. Based on a small size system, the PAM concept is introduced. The study is performed upon time-domain simulations and analytical formulations of the power transfer equations. Additionally, the IEEE 9 BUS system and the test model of Great Britain’s system are used to further investigate the performance of the PAM controller in a multi-machine context, as well as to perform a comparative assessment of the effect of different fault locations, and the necessary wind generators that should be equipped with PAM controllers.
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47

Samuel, Oluwarotimi Williams, Mumini Olatunji Omisore, and Edafe John Atajeromavwo. "Online fuzzy based decision support system for human resource performance appraisal." Measurement 55 (September 2014): 452–61. http://dx.doi.org/10.1016/j.measurement.2014.05.024.

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48

Nguyen, Frank. "What you already know does matter: Expertise and electronic performance support systems." Performance Improvement 45, no. 4 (April 2006): 9–12. http://dx.doi.org/10.1002/pfi.2006.4930450404.

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49

Kert, Serhat Bahadır, and Adile Aşkım Kurt. "The effect of electronic performance support systems on self-regulated learning skills." Interactive Learning Environments 20, no. 6 (June 8, 2011): 485–500. http://dx.doi.org/10.1080/10494820.2010.533683.

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Laffey, James. "Dynamism in Electronic Performance Support Systems Originally published in 1995, PIQ 8.1." Performance Improvement Quarterly 10, no. 1 (October 22, 2008): 183–98. http://dx.doi.org/10.1111/j.1937-8327.1997.tb00038.x.

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