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A study on search system for e-learning products

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  1. Abstract
  2. Introduction
  3. Theoretical foundations
    1. E-learning
    2. Extended TAM
    3. Multiple
  4. Research Methodology
    1. Research model and hypotheses
    2. Measurement variables
    3. Data collection
    4. Reliability and factor analysis
    5. Structural equation results
  5. E-learning product search system (ELSS)
  6. Central processing agent using BP
  7. Conclusion
  8. References

In this paper, we propose the E-learning product search system (ELSS) which can provides high quality information fitted to the learners' demands. ELSS can also provide the accurate information that doesn't contain unnecessary information in mass e-learning products on the internet. Through multiple agents, this system extracts the optimal output based on input data such as learner's demands and interests. In addition, BP (Back Propagation) algorithm is applied to the multiple agents to obtain optimal results. Input variables are designed by Extended TAM (Technology Acceptance Model) for the high reliability of ELSS. The factors that learners consider when choosing E-learning products are analyzed by extended TAM and the factors are extracted by SEM (Structural Equation Model) analysis. After the appearance of the internet, our life style has been remarkably changed. Shopping, financial payment and commercial transaction on the Web are revitalized and the circulation of personal knowledge and creating information has become major flow on the Web. In this new area, the number of people offering or receiving information and knowledge has been increased.

[...] Table 1 Summary of measurement variables Measurement variables Perceived usefulness Perceived ease of use Perceived enjoy Reputation Individual preference Functional service Price Economy of time Marketing Behavioral intention Real Behavior Choose a e-learning product Definition The degree of intention to adopt e-learning will be The convenience of e-learning contents and service The extent to which the activity of using the e-learning is perceived to be enjoyable Opinion or view one about e-learning Contents visual impressions, recommend lecturer Service and contents speed, service efficiency The package price/rate Free from time, economy of moving time Discounts, events, and marketing The behavior intention toward e-learning A learner's real behavior on e-learning The existent e-learning product (Output data of BP) Scale The rating of input variables was based on a scale of being best and 1 worst Multiple-Choice 3.3 Data collection We surveyed people who can easily access the internet and have experience in using E-learning service questionnaires were distributed and 176 questionnaires were analyzed except 24 questionnaires which were incomplete and un-filled Reliability and Factor analysis Before studying SEM, we carried reliability and factor analysis out for internal consistency and validation. [...]


[...] E-learning product search system (ELSS) ELSS is a system which analyzes demands from learners and recommend proper E -learning product. ELSS is designed for the multiple agent which consists of 6 agents. ELSS has a same construction with Fig Personal Agent A personal agent conveys data received from learners to the integrated data store agent. UI consists of facts from SEM analysis using Extended TAM. For receiving learner's exact tastes and demands, this agent design s UI of categories of E-learning and a question form. [...]


[...] TAM is a way for grasping the interrelation behavior intention to use or get a line on influence factors of the technical attitude. TAM is based on the Theory of Reasoned Action (TRA) introduced by Fishbein and Ajzen. TRA regards an attitude as the sum of the conviction, intention and action. In addition, it includes social aspects of the attitude. Actually, this theory predicts not the attitude but the intention of the attitude. So it assumes that the intention and the attitude are nearly same under a proper condition. [...]

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