Real-life problem solving: A collaborative approach to interdisciplinary learning.

This paper clearly explains the concept, importance and main aim of machine learning and construction of the machine learning system. There are several ideas regarding this machine learning which are formed by a number of strategies. This effort leads to introduce many machine learning methods such as learning by commands, concept, learning by comparison, and learning by some algorithms. This article provides information about the main purpose of machine learning and its development. Machine learning is the primary aspect that promotes any system to have intelligence. One of its main applications is artificial intelligence. Machine learning is highly suited for complex level system representation. There are a number of machine learning concepts that leads to the integration of number of networks.

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The impact of situated learning activities on technology university students' learning outcome

Education + Training ◽

10.1108/et-04-2018-0092 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Hua-Huei Chiou

Keyword(s):

Problem Solving ◽

Child Development ◽

University Students ◽

Situated Learning ◽

Real Life ◽

Learning Outcome ◽

Learning Activities ◽

Live Video ◽

Content Type ◽

Real Life Problem

PurposeThe purpose of this study was to investigate 3D virtual reality (VR) situated activity, preschool reality and how the lecture teaching method affects technology university students' learning outcome.Design/methodology/approachThe quasi-experimental design is used. Participants are 144 students in three classes who all take Child Development Assessment course. Research instruments include 3D VR animation, preschool live video and child development as the case. One class attended 3D VR situated activities, another observed preschool live video and the other takes a traditional lecture class. Learning outcomes were measured by two paper-and-pencil tests in different times and with one performance assessment. In the writing test, mechanical and meaningful questions were included.FindingsMajor findings of this study are, first, that the auxiliary learning of 3D VR is better than the real-life situation. Second, situational learning activities can enhance participant performance in context-based questions. In summary, this study found that well-organized 3D VR animation is more effective than live situation learning, especially for context-based course content.Research limitations/implicationsThe lack of random assignment into test groups leads to non-equivalent test groups which can limit the generalizability of the results to other student population.Practical implicationsThe findings of this study suggest that teachers can gradually arrange learning activities, from 3D VR to a real applied workplace; situated learning activities are more likely to support the transfer knowledge to real-life problem solving.Originality/valueThe findings suggest that teachers in arranging the classroom context activities can be the first to use 3D VR before actual reality to avoid novices getting lost in the complicated real situations. If learning activities can be arranged gradually, from 3D VR to real applied workplace, situated learning activities can help students to deploy their newly acquired knowledge and skills in real-life problem solving.

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