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Titlebook: Innovation in Information Systems and Technologies to Support Learning Research; Proceedings of EMENA Mohammed Serrhini,Carla Silva,Sultan

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樓主: magnify
41#
發(fā)表于 2025-3-28 15:16:30 | 只看該作者
Classification of Learners During an Educational Simulation: Case Study on a Stock Management Simuldentifying the learner’s group could help the teacher to provide customised advice and thus improve overall learning. This study throws light on the link between the learners’ traces, motivations and performances of learner in a real learning situation. First, we discovered occurrences of a “followe
42#
發(fā)表于 2025-3-28 19:56:13 | 只看該作者
A Machine Learning Model to Early Detect Low Performing Students from LMS Logged Interactions,something nearly impossible to achieve. With the increasing integration of Learning Management Systems in education, grade prediction seems to have become a viable option. The general adoption of this type of systems brings to the research area a database known as “registry”, or more simply known as
43#
發(fā)表于 2025-3-29 02:29:33 | 只看該作者
44#
發(fā)表于 2025-3-29 05:28:40 | 只看該作者
45#
發(fā)表于 2025-3-29 07:34:56 | 只看該作者
Graph Schema Storage in SQL Object-Relational Database and NoSQL Document-Oriented Database: A Compdatabases were sufficient in the first time, but with the evolution of computer science technologies, other factors start to appear; such as the volume of the stored data, the velocity of the transactions between the user and data, the possibility to store heterogeneous data (variety) and many other
46#
發(fā)表于 2025-3-29 14:36:38 | 只看該作者
47#
發(fā)表于 2025-3-29 16:38:54 | 只看該作者
48#
發(fā)表于 2025-3-29 22:01:45 | 只看該作者
Analysis of ESP32 SoC for Feed-Forward Neural Network Applications,has been analysed because some companies started to produce them with UXGA camera implemented and it can be used to distribute computing load from central ML servers to them. They can be so-called “edge” devices and in this paper speed of ESP32 SoC in feed-forward mode has been analysed.
49#
發(fā)表于 2025-3-30 00:13:41 | 只看該作者
50#
發(fā)表于 2025-3-30 06:19:29 | 只看該作者
Modeling the Acceptance of the E-Orientation Systems by Using the Predictions Algorithms,ng, individual interviews in collaborations with the experts in the field of orientation. After we collected the feedback from our study sample, we use the information gain attribute to reduce our data and we apply applied and compare several predictive Machine Learning algorithms to select the best one with the highest accuracy.
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