APPLICATION OF GAMIFICATION IN INTRODUCTION TO PROGRAMMING: A CASE STUDY

Institution of higher educations has struggled to provide engaging method to learn programming although effort has been made by educators but often with limited success. The question is how best to teach introductory to programming for novices students is often not addressed properly. This is because learning programming for college students especially for new learners in programming present many challenges such as subject difficulty, lack of motivation in doing exercises, passiveness in class and diversity of student abilities. Since students often faced a lot of difficulties when learning introductory of programming, gamification has the potential to provide a way to promote students’ motivation and engagement while also providing feedback on the students’ level of competency of the learned material. Gamification is the process of incorporating game elements into education in an effort to increase student engagement.Thus, there appears to be a good fit between introductory of programming and gamification. Taking these elements into consideration, this paper seeks to apply the concept of gamification to semester 1 students taking Java Programming as the first level of programming subject.  Some best practices in gamification such as competitions, incorporating engaging games elements, scoring using rewards and levels, badges, providing feedback, and providing homework to encourage informal learning are going to be applied. Finally, several popular online applications such as Kahoot, Online Crossword Puzzle and Online Quiz were also designed to see the impact on these gamification tools towards learning of students. The game would be designed to have 3 levels that increase in difficulties with competition as a core element to increase student’s engagement. This paper would also seeks to design the  user evaluation form that can be  used to  determine the effects of applying gamification on the student’s engagement, motivation level, and understanding of the topic in introductory programming subject. Through the research findings it could provide a platform in formulating alternative ways besides the traditional teaching method for educators in creating educational programming games and applying it to teach novices in introductory programming subjects.&nbsp

Triad Role in Shaping Tanzanian Pre-service Teachers\u27 Experience of Teaching Practice

This study explores the role of the triad relationship in shaping pre-service teachers’ experience during teaching practice. The study is descriptive in nature employing a qualitative approach and data from a sample of five pre-service teachers, five college supervisors, five mentor teachers and three Heads of school. The data were analysed through thematic analysis. The findings revealed that limited triad relationship, limited social and instructional support from mentor teachers and supervisors’ limited assessment and feedback provision, negatively impacted pre-service teachers’ learning during teaching practice. To achieve a functioning triad the paper suggests that it is important to equally engage supervisors, mentor teachers and Heads of school in formulating appropriate support practices for pre-service teachers. Such practice may include implementing a feedback process where all members of the triad come together

Kecenderungan Keusahawanan di Kalangan Pelajar Bidang Kejuruteraan di Institusi Pengajian Tinggi Awam di Kawasan Utara Semenanjung Malaysia

The field of entrepreneurship is fast developing in line with the government support for Malaysian to adopt entrepreneurship as their career choice. The study was conducted to determine whether the final year students in the area of engineering at the public Institute of Higher Learning (IHL) have the intention to become entrepreneur upon graduation. The study focuses on the final year undergraduates in the area of engineering from public IHL in the northern region of Malaysia. The IHL chosen were Universiti Sains Malaysia Transkrian (USM), Universiti Teknologi Mara (UiTM) Pulau Pinang and Universiti Malaysia Perlis (UniMap). The study conducted was based on the Theory of Planned Behaviour that includes the individual attitude, subjective norms and perceived behavioural control towards entrepreneurship. The instrument used for the study was The Entrepreneurial Intention Questionnaire (EIQ) developed by Linan, Urbano dan Guerrero (2007).Data were collected using a set of questionnaire. Results from the study shows that there were positive and significant relationship between the exposure to the entrepreneurship courses and the entrepreneurial intention. It was also found that there were positive and significant relationship between personal attraction, subjective norm, perceived behavioral control, closure value and social value with the intention toward entrepreneurship. From the study, it was found that the engineering undergraduates as a whole have the intention toward entrepreneurship.With more attention, support and exposure given to them, the possibilities of the engineering students becoming entrepreneurs is eminent upon their graduation

EFFECT OF CERTAIN PROCESSING METHODS ON PHOSPHOLIPID COMPONENTS IN RABBIT MEAT

Fore limb, loin and hind limb cuts of California and New Zealand white rabbits (both sexes) of a marketable age (2 and 3 months) were used to study the effect of certain processing methods (pressure cooking, roasting and smoking) on phospholipid components in rabbit meat. Phospholipids were fractionated applying thin-layer chromatographic (TLC) tech- nique to eight fractions (phosphatidylserine (PS), lysophosphatidylcholine (LPC), phos- phatidyl inositol (PI), sphingomyelin (SL), phosphatidylcholine (PC), phosphatidyl ethanolamine (PE), phosphatidic acid (PA) and phosphatidyl glycerol (PG)). Rather slight differences were observed between sexes, ages and three studied cuts in the quantities of phospholipid components. Phospholipid fractions showed qualitatively the same pattern as that of fresh meat in the three studied processing methods of rabbit meat. However, all studied processing methods resulted in a decrease in all phospholipid fraction contents, except that of Iysophosphatidyl choline and (phosphatidic acid + phosphatidyl glycerol) which slightly increased

Insight of recent strategies and initiatives in managing integrity in Malaysia

The Malaysian government has taken several steps to combat corruption and nurture integrity in society, especially among civil servants. There are many key strategies aimed at fostering and enhancing a culture of integrity, thus, the Malaysian government has agreed to align all efforts on governance, dignity, and anti-corruption into a single integrated plan to strengthen anti-corruption initiatives. The National Anti-Corruption Plan (NACP) was created and demonstrated to achieve the Sustainable Development Goals (SDG-16) that focuses on Peace, Justice, and Strong Institutions. The purpose of this study is to provide an overview of recent strategies and initiatives in managing integrity in Malaysia and to evaluate the integrity behavior among public sector employees. The online questionnaire surveys were distributed to collect the primary data. About 100 employees were randomly selected among civil servants in Malaysia, and yielded a response rate of 77% (77 respondents). The data was then analyzed using SPSS to achieve the objectives; thus, descriptive statistics and Pearson correlation were used to analyze the study variables. The finding indicated that there is a significant relationship between anti-corruption plans and managing integrity among employees in Malaysia. This study will help policymakers to take necessary action to ensure the long-term continuity of the policies and action plans implemented to create a corrupt-free nation that values integrity. It will give value in achieving the SDG-16 goal to substantially reduce bribery and corruption in all their forms

A survey on technique for solving web page classification problem

Nowadays, the number of web pages on the World Wide Web has been increasing due to the popularity of the Internet usage. The web page classification is needed in order to organize the increasing number of web pages. There are many web page classification techniques that have been proposed by the other researchers. However, there is no comprehensive survey on the performance of the techniques for the web page classification. In this paper, surveys of the different web page classification techniques with the result of the techniques achieved are presented. The existing works of web page classification are reviewed. Based on the survey, we found that the neural network technique namely Convolutional Neural Network (CNN) produce high F-measure value and meet the real-time requirement for classification compared to the other machine learning technique

Data pre-processing of website browsing record: An initial step for web page classification

The Internet utilization has resulted in an increase in the number of web pages on the World Wide Web. The classification of web pages is required to organize the growing number of web pages. A web page classification system is proposed to be constructed using a deep learning algorithm. The initial step for web page classification is data pre-processing. The website browsing record is used as a dataset in this study. The raw dataset needs to be pre-processing to fetch the cleaned data by removing missing value data, redundant data, and error data. There are many steps in data pre-processing which include data cleaning and web content pre-processing. The main contribution of this paper is to investigate how to do data pre-processing on website browsing records that focusing on the Game and Online Video web pages that will be utilized as the dataset to construct the web page classification model. After doing the data pre-processing, the number of datasets will be reduced. This shows many datasets have been removed because it is inactive and not suitable to be used in this study as the dataset of Game and Online Video web pages

A model of web page classification using convolutional neural network (CNN): a tool to prevent internet addiction

Game and Online Video Streaming are the most frequently visited web pages. Internet addiction may be negatively impacted by users who spend too much time on these types of web pages. Access to Game and Online Video Streaming web pages needs to be limited in order to combat the issue of internet addiction. Therefore, a tool that can categorize incoming web pages based on their content is required. This paper is proposing a web page classification model using a Convolutional Neural Network (CNN) to classify the web page whether it is a Game or Online Video Streaming based on the pattern of words in the word cloud image generated from the web page text content. The proposed web page classification model has achieved 85.6% accuracy

Use Word Cloud Image Of Web Page Text Content On Convolutional Neural Network (CNN) For Classification Of Web Pages

In today's environment, people can easily use the internet to find information by visiting web pages. Most people like to visit web pages that offer games and videos to watch online. People who spend a lot of time on web pages like these can become addicted to the internet and it can have a bad effect on them. Access to web pages that offer games and streaming videos needs to be limited to stop people from being addicted to the internet. It needs a tool that can classify web pages category based on its content. Due to lack of matrix representation that unable to handle long web page text content, this study uses a technique which is word cloud image to visualize the words that has been extracted from the text content web page after performing data pre-processing. The most popular words from the text content web page are displayed in big size and appear in center of the word cloud image. The most popular words are the words that frequently appear in the text content web page, and it related to describe what the web page content is about. The Convolutional Neural Network (CNN) identifies the pattern of words displayed in the central areas of the word cloud image to classify the category that the web page belongs to. The proposed model for classifying web pages has an accuracy of 0.86. The proposed model can be used, for example, by the institution to set rules and limit the usage of the internet for the users to surf the web pages that offer games and streaming videos. It will be one of the ways to prevent users from getting internet addiction

A Convolutional Neural Network (CNN) Classification Model for Web Page: A Tool for Improving Web Page Category Detection Accuracy

Game and Online Video Streaming are the most viewed web pages. Users who spend too much time on these types of web pages may suffer from internet addiction. Access to Game and Online Video Streaming web pages should be restricted to combat internet addiction. A tool is required to recognise the category of web pages based on the text content of the web pages. Due to the unavailability of a matrix representation that can handle long web page text content, this study employs a document representation known as word cloud image to visualise the words extracted from the text content web page after data pre-processing. The most popular words are shown in large size and appear in the centre of the word cloud image. The most common words are the words that appear frequently in the text content web page and are related to describing what the web page content is about. The Convolutional Neural Network (CNN) recognises the pattern of words presented in the core portions of the word cloud image to categorise the category to which the web page belongs. The proposed model for web page classification has been compared with the other web page classification models. It shows the good result that achieved an accuracy of 85.6%. It can be used as a tool that helps to make identifying the category of web pages more accurat