Thank you for reading learning to teach in higher education. As you may know, people have look numerous times for their favorite books like this learning to teach in higher education, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some infectious bugs inside their laptop. learning to teach in higher education is available in our digital library an online access to it is set as public so you can get it instantly. Our book servers spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the learning to teach in higher education is universally compatible with any devices to read.

Learning To Teach In Higher Education

Learning the lessons.

Code duplication or copying a code fragment and then reuse by pasting with or without any modiflcations is a well known code smell in software maintenance. Several studies show that about 5% to 20% of a software systems can contain duplicated code, which is basically the results of copying existing code fragments and using then by pasting with or without minor modiflcations. One of the major shortcomings of such duplicated fragments is that if a bug is detected in a code fragment, all the other fragments similar to it should be investigated to check the possible existence of the same bug in the similar fragments. Refactoring of the duplicated code is another prime issue in software maintenance although several studies claim that refactoring of certain clones are not desirable and there is a risk of removing them. However, it is also widely agreed that clones should at least be detected. In this paper, we survey the state of the art in clone detection research. First, we describe the clone terms commonly used in the literature along with their corresponding mappings to the commonly used clone types. Second, we provide a review of the existing clone taxonomies, detection approaches and experimental evaluations of clone detection tools. Applications of clone detection research to other domains of software engineering and in the same time how other domain can assist clone detection research have also been pointed out. Finally, this paper concludes by pointing out several open problems related to clone detection research.

/pdf/a-survey-on-software-clone-detection-research-3hmh7abinb.pdf

A Survey on Software Clone Detection Research

ONE of the most remarkable examples of sudden and rapid development of a new scientific method and a new and extensive body of scientific fact is to be seen in the growth of the study of animal psychology during the last ten or a dozen years. As in the case of the general science of psychology, the change came with the introduction of experiment as the fundamental method of investigation, but the transition was accentuated by a craving for objectivity of results, which focussed the attention upon the objective performance or behaviour of the animal under examination, not only to the detriment, but even, in the case of many observers, to the complete neglect of speculation as to its psychical life. If the new psychology claimed to be a psychology without a soul, the new animal psychology threatened, and still threatens, to become an animal psychology without consciousness. Many investigators have indeed openly declared for this ideal-not denying the presence of consciousness, but regarding it as of no importance or value in an explanatory scientific system. Nevertheless signs are not wanting in the most recent work of a healthy reaction from this extreme view, based as much upon observed fact as upon a priori speculation. Animal Intelligence: Experimental Studies. By E. L. Thorndike. Pp. viii + 297. (New York: The Macmillan Co.; London: Macmillan and Co., Ltd., 1911.) Price 7s. net.

Animal Intelligence: Experimental Studies

It represents a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use.

/pdf/computational-thinking-ji-suan-lun-de-si-kao-3qvv34ha3s.pdf

Computational Thinking 計算論的思考

This chapter reviews the issues associated with contract cheating, loosely defined as the outsourcing of student work to third parties. The chapter is intended to serve as an overview of current research while also providing practical instruction and guidance to academics and educators The discussion begins by introducing contract cheating and comparing this specific form of academic misconduct with student plagiarism. The suggestion is made that current anti-plagiarism methods are not suitable for contract cheating, defined as where a student is requesting an original bespoke piece of work to be created for them. Six types of services that students can use to have work produced for them are listed; these are (1) essay writing services; (2) friends, family, and other students; (3) private tutors; (4) copyediting services; (5) agency websites; and (6) reverse classifieds. Specific challenges associated with each service are provided. Findings related to the wider contract cheating area are given. This includes particular discussion of the research into agency sites, where a student makes the offer of work available to a large number of people who then bid to complete it. The student selects one of the bidders to complete the work based on a form of cost-benefit analysis. Issues considered include the extent of contract cheating, the cost and quality of outsourced work, and the range of subjects in which students are cheating The chapter concludes with a discussion of the main methods that can be used to prevent contract cheating. Research into technical solutions, such as stylometrics, put in place to find automated technical solutions to detect contract cheating, is also presented. © Springer Science+Business Media Singapore 2016.

Contract cheating: The outsourcing of assessed student work

Automated techniques for finding plagiarism in student source code submissions have been in use for over 20 years and there are many available engines and services. This paper reviews the literature on the major modern detection engines, providing a comparison of them based upon the metrics and techniques they deploy. Generally the most common and effective techniques are seen to involve tokenising student submissions then searching pairs of submissions for long common substrings, an example of what is defined to be a paired structural metric. Computing academics are recommended to use one of the two Web-based detection engines, MOSS and JPlag. It is shown that whilst detection is well established there are still places where further research would be useful, particularly where visual support of the investigation process is possible.

A Comparison of Source Code Plagiarism Detection Engines

Students are using file sharing sites to breach academic integrity in light of the Covid-19 pandemic This paper analyses the use of one such site, Chegg, which offers “homework help” and other academic services to students Chegg is often presented as a file sharing site in the academic literature, but that is just one of many ways in which it can be used As this paper demonstrates, Chegg can and is used for contract cheating This is despite the apparent existence of an Honour Code on Chegg which asks students not to breach academic integrity With pandemic led safety considerations leading to increased online teaching and assessment, the paper analyses data relating to how Chegg is used by students in five STEM subjects, namely Computer Science, Mechanical Engineering, Electrical Engineering, Physics and Chemistry The results show that students are using Chegg to request exam style questions They demonstrate that contract cheating requests can be put live and answered within the short duration of an examination The number of student requests posted for these five subjects increased by 19625% comparing the time period April 2019 to August 2019 with the period April 2020 to August 2020 This increase corresponds with the time when many courses moved to be delivered and assessed online The growing number of requests indicates that students are using Chegg for assessment and exam help frequently and in a way that is not considered permissible by universities The paper concludes by recommending that academic institutions put interventions in place to minimise the risk to educational standards posed by sites such as Chegg, particularly since increased online teaching and assessment may continue after the pandemic

/pdf/contract-cheating-by-stem-students-through-a-file-sharing-37k8vbai4q.pdf

Contract cheating by STEM students through a file sharing website: a Covid-19 pandemic perspective

This study examines the reasons students give for seeking unacceptable levels of help with completion of their academic work. It aims to fill the gap in the literature by presenting a comprehensive review of the first-person reasons students have given for requesting that someone else completes their assignments and assessments for them. To this end, we analyzed a dataset composed of 5,000 messages from ten contract cheating services posted on the social media service Twitter. Unlike survey research that relies on participants' ability to recall and explain the events, this study uses discourse analysis that provides a snapshot of student behaviors from the moment they announce their intent to outsource the work, an area that has not previously been analyzed in the contract cheating research base. The reasons accompanying the solicitation of contract work were classified into five categories that include: academic aptitude, perseverance, personal issues, competing objectives, and self-discipline. One important insight of this study is that students appear to have a subjective threshold; they are willing to invest a certain amount of energy in any given assignment, and once the limit is reached outsourcing is sought as the means to quit without losing the qualification. Recommendations for addressing the issue of contract cheating and directions for future research are discussed.

246 reasons to cheat: An analysis of students’ reasons for seeking to outsource academic work

Academic institutions are finding they have to operate under a pro‐active anti‐plagiarism policy, where plagiarism is actively sought out as a serious breach of acceptable academic behaviour. This paper considers the reasons that institutions need such a policy and the issues they should be aware of when implementing one.

Thomas Lancaster

Papers

Contract cheating: The outsourcing of assessed student work

A Comparison of Source Code Plagiarism Detection Engines

Contract cheating by STEM students through a file sharing website: a Covid-19 pandemic perspective

246 reasons to cheat: An analysis of students’ reasons for seeking to outsource academic work

Plagiarism issues for higher education