Programming Learning Requirements Based on Multi Perspectives

Khaleel, Firas Layth; Sahari, Noraidah; Wook, Tengku Siti Meriam Tengku; Ismail, Amiruddin

doi:10.11591/ijece.v7i3.pp1299-1307

Cited by 11 publications

(9 citation statements)

References 30 publications

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“…Consequently, [4][5][6][7] elucidated that an strategy which can effortlessly amplify the engagements and applied in an exciting manner (such as games like elements) ought to be adopted in gaining knowledge of difficult subjects. Gamification refers to the use of recreation factors in a non-game context to expand engagement between human beings and computer systems and to clear up troubles correctly [8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

The impact of gamification on students learning engagement

Khaleel

Sahari

Wook

2020

IJECE

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Gamification is to use game elements in a non-game context to increase engagement between human and computer, on the other hand, to encourage in-demand for good behaviors in learning. This research tried to increase student engagements in learning by conducted Gamification technique especially in difficult subjects such as Programming Language courses. The previous work was shown that students dropped, failed, or withdrew from the course at rates of between 35% and 50%. Therefore the main objective of this study is to increase student engagements in learning programming subject, and also to measure the impact of game elements on student’s engagements. Finally, the findings have shown the score of game elements that have a good effect on student’s engagement in the experiment group.

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Section: Introductionmentioning

confidence: 99%

The impact of gamification on students learning engagement

Khaleel

Sahari

Wook

2020

IJECE

Self Cite

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“…This is a scalable and fast big data processing engine that was first developed by the AMPLab at the University of California, Berkeley [93]- [95]. It may be used to construct distributed applications in a variety of computer languages, including Java, Python, and other programming languages [96]- [105]. When it is installed, it includes four major libraries: Apache Spark structured query language (SQL), Apache Spark Streaming, Apache Spark MLlib, and Apache Spark GraphX.…”

Section: Apache Spark Mllib 20mentioning

confidence: 99%

Large scale data analysis using MLlib

et al. 2021

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Recent advancements in the internet, social media, and internet of things (IoT) devices have significantly increased the amount of data generated in a variety of formats. The data must be converted into formats that is easily handled by the data analysis techniques. It is mathematically and physically expensive to apply machine learning algorithms to big and complicated data sets. It is a resource-intensive process that necessitates a huge amount of logical and physical resources. Machine learning is a sophisticated data analytics technology that has gained in importance as a result of the massive amount of data generated daily that needs to be examined. Apache Spark machine learning library (MLlib) is one of the big data analysis platforms that provides a variety of outstanding functions for various machine learning tasks, spanning from classification to regression and dimension reduction. From a computational standpoint, this research investigated Apache Spark MLlib 2.0 as an open source, autonomous, scalable, and distributed learning library. Several real-world machine learning experiments are carried out in order to evaluate the properties of the platform on a qualitative and quantitative level. Some of the fundamental concepts and approaches for developing a scalable data model in a distributed environment are also discussed.

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“…The results of the study (Khaleel et al, 2017) show that the low value of learning programming is because students experience ineffective learning, lack of interest and lack of motivation. Another most important problem faced by students in learning programming is in the practicum section, which involves their need to practice extensively to achieve higher programming skills (Wei, 2010).…”

Section: Introductionmentioning

confidence: 98%

An Overviuw Of The Teaching And Learning Process Basic Programming In Algorithm And Programming Courses

Susanti¹

2021

TURCOMAT

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In this paper, we review the literature related to computer programming learning, where Algorithms and Programming are the topic domains of the Informatics and Computer science clusters. There are 4 competencies in learning outcomes, such as: 1) understand algorithmic concepts; 2) master algorithm concepts and principles; 3) master programming language concepts; and 4) master programming languages and algorithms. The main focus of this review is on beginner programming and topics related to student difficulties in learning programming. Various problems experienced by beginners were identified from the literature to some of the solutions offered by researchers.

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Programming Learning Requirements Based on Multi Perspectives

Cited by 11 publications

References 30 publications

The impact of gamification on students learning engagement

The impact of gamification on students learning engagement

Large scale data analysis using MLlib

An Overviuw Of The Teaching And Learning Process Basic Programming In Algorithm And Programming Courses

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