Currently there are standards at the level of technological infrastructure to support e-learning. But cunato processes and procedures to improve the quality of elearning, not yet been identified standards or management models. From there the importance of this question.
A Roadmap to Quality in E-Learning:
Control charts are a key tool in interpreting data in E-learning. They can distinguish between dispersions caused by accidental factors and dispersions caused by abnormal factors, and can show whether the process is in a stable condition or not. A control chart consists of a central line (CL) and upper and lower control limits (UCL and LCL). UCLs and LCLs are based on calculated values.
There are several kinds of control chart:
A1. x–-R control charts (average and range).
These are used in the management of variable data. x– and R represent a sub-group average and sub-group range respectively. The x– control charts are used for monitoring changes in the sub-group average (variation among sub-groups), while the R control charts are used for managing dispersions within a sub-group (variation within a sub group). These two charts are paired for use.
A2. “p” control charts and “pn” control charts:
These manage processes in which the characteristic values of discrete values are considered. “pn” control charts are used when the number of samples (n) is constant and the number of defective units (pn) is considered. When the number of samples (n) is not constant, in other words when the ratio of defects (p) is considered, “p” control charts are used.
A3. “c” control charts (defects per unit) or “u” control charts (standard defects per unit) may be used depending on the characteristics of measured values.
We know that evaluation is important for an instructional design
http://www.learningsolutionsmag.com/assets/images/learningsolutions/040504/040504mgt-fig1pg3.png
Thanks for your reply, in this regard we rely all concerned to better recognize these models.
Hi Ariel
Please refer to:
· Information Management Model for Intellectual Capital of HEIs in Oman: Theoretical Quantitative Approach and Practical Results. J. of Information and Knowledge Management, 2018, Vol. 17, No. 1, pp.1-38. (World Scientific).
· HEIs Quality Improvement Through Students and Academic Staff’s Perception: Data Analysis and Robustness of the Results. International Journal for Quality Research, 2017, Vol.11, No.2, pp.261-278.
· Al-Farahidi Performative model to assess HEIs. 4th OQNHE Conference 2017, pp.1-15.
· A Framework for Fostering the Quality of HEIs: Data Collection, Evaluation, Indication and Validation. Int. J. of Quality and Innovation, 2016, Vol.3, No.1, pp.42-66 (Inderscience).
Regards,
Zuhair
In addition, the following paper may useful for your research,
Bolboli, S. A. and Reiche , M. (2015), “Introducing a concept for efficient design of EFQM excellence model”, The TQM Journal, Vol. 27, Iss. 4, pp.382 – 396.
Bolormaa Demchig (2015). Knowledge management capability level assessment of the higher education institutions: Case study from Mongolia. Procedia - Social and Behavioral Sciences 174 ( 2015), pp.3633 – 3640.
