Academic literature on the topic 'Computer programming Study and teaching (Higher) Case studies'

Edmodo is becoming increasingly used in higher education. It helps teachers to easily share learning content with students, and communicate with them better. Several studies demonstrate its effectiveness in improving students’ results and satisfaction with the learning process. In this paper, we describe our experience using Edmodo for courses in computer sciences designed for engineering students. We tested Edmodo in three courses delivered in a blended learning mode: the assembly language programming, the operating systems, and the PHP language programming. The learning scenario adopted for these courses was already presented in our previous work on the pedagogy of integration. Results show that the use of Edmodo within the pedagogy of integration enhances both learning and teaching experiences.

Artificial intelligence (AI) has the potential to speed up the exponential growth of cutting-edge technology, much way the Internet did. Due to intense competition from the private sector, governments, and businesspeople around the world, the Internet has already reached its peak as an exponential technology. In contrast, artificial intelligence is still in its infancy, and people all over the world are unsure of how it will impact their lives in the future. Artificial intelligence, is a field of technology that enables robots and computer programmes to mimic human intellect by teaching a predetermined set of software rules to learn by repetitive learning from experience and slowly moving toward maximum performance. Although this intelligence is still developing, it has already demonstrated five different levels of independence. Utilized initially to resolve issues. Next, think about solutions. Third, respond to inquiries. Fourth, use data analytics to generate forecasts. Fifth, make tactical recommendations. Massive data sets and "iterative algorithms," which use lookup tables and other data structures like stacks and queues to solve issues, make all of this possible. Iteration is a strategy where software rules are regularly adjusted to patterns in the data for a certain number of iterations. The artificial intelligence continuously makes small, incremental improvements that result in exponential growth, which enables the computer to become incredibly proficient at whatever it is trained to do. For each round of data processing, the artificial intelligence tests and measures its performance to develop new expertise. In order to address complicated problems, artificial intelligence aims to create computer systems that can mimic human behavior and exhibit human-like thought processes [1]. Artificial intelligence technology is being developed to give individualized medication in the field of healthcare. By 2030, six different artificial intelligence sectors will have considerably improved healthcare delivery through the utilization of larger, more accessible data sets. The first is machine learning. This area of artificial intelligence learns automatically and produces improved results based on identifying patterns in the data, gaining new insights, and enhancing the outcomes of whatever activity the system is intended to accomplish. It does this without being trained to learn a particular topic. Here are several instances of machine learning in the healthcare industry. The first is the IBM Watson Genomics, which aids in rapid disease diagnosis and identification by fusing cognitive computing with genome-based tumour sequencing. Second, a project called Nave Bayes allows for the prediction of diabetes years before an official diagnosis, before it results in harm to the kidneys, the heart, and the nerves. Third, employing two machine learning approaches termed classification and clustering to analyse the Indian Liver Patient Data (ILPD) set in order to predict liver illness before this organ that regulates metabolism becomes susceptible to chronic hepatitis, liver cancer, and cirrhosis [2]. Second, deep learning. Deep learning employs artificial intelligence to learn from data processing, much like machine learning does. Deep learning, on the other hand, makes use of synthetic neural networks that mimic human brain function to analyse data, identify relationships between the data, and provide outputs based on positive and negative reinforcement. For instance, in the fields of Magnetic Resonance Imaging (MRI) and Computed Tomography (CT), deep learning aids in the processes of picture recognition and object detection. Deep learning algorithms for the early identification of Alzheimer's, diabetic retinopathy, and breast nodule ultrasound detection are three applications of this cutting-edge technology in the real world. Future developments in deep learning will make considerable improvements in pathology and radiology pictures [3]. Third, neural networks. The artificial intelligence system can now accept massive data sets, find patterns within the data, and respond to queries regarding the information processed because the computer learning process resembles a network of neurons in the human brain. Let's examine a few application examples that are now applicable to the healthcare sector. According to studies from John Hopkins University, surgical errors are a major contributor to medical malpractice claims since they happen more than 4,000 times a year in just the United States due to the human error of surgeons. Neural networks can be used in robot-assisted surgery to model and plan procedures, evaluate the abilities of the surgeon, and streamline surgical activities. In one study of 379 orthopaedic patients, it was discovered that robotic surgery using neural networks results in five times fewer complications than surgery performed by a single surgeon. Another application of neural networks is in visualising diagnostics, which was proven to physicians by Harvard University researchers who inserted an image of a gorilla to x-rays. Of the radiologists who saw the images, 83% did not recognise the gorilla. The Houston Medical Research Institute has created a breast cancer early detection programme that can analyse mammograms with 99 percent accuracy and offer diagnostic information 30 times faster than a human [4]. Cognitive computing is the fourth. Aims to replicate the way people and machines interact, showing how a computer may operate like the human brain when handling challenging tasks like text, speech, or image analysis. Large volumes of patient data have been analysed, with the majority of the research to date focusing on cancer, diabetes, and cardiovascular disease. Companies like Google, IBM, Facebook, and Apple have shown interest in this work. Cognitive computing made up the greatest component of the artificial market in 2020, with 39% of the total [5]. Hospitals made up 42% of the market for cognitive computing end users because of the rising demand for individualised medical data. IBM invested more than $1 billion on the development of the WATSON analytics platform ecosystem and collaboration with startups committed to creating various cloud and application-based systems for the healthcare business in 2014 because it predicted the demand for cognitive computing in this sector. Natural Language Processing (NLP) is the fifth. This area of artificial intelligence enables computers to comprehend and analyse spoken language. The initial phase of this pre-processing is to divide the data up into more manageable semantic units, which merely makes the information simpler for the NLP system to understand. Clinical trial development is experiencing exponential expansion in the healthcare sector thanks to NLP. First, the NLP uses speech-to-text dictation and structured data entry to extract clinical data at the point of care, reducing the need for manual assessment of complex clinical paperwork. Second, using NLP technology, healthcare professionals can automatically examine enormous amounts of unstructured clinical and patient data to select the most suitable patients for clinical trials, perhaps leading to an improvement in the patients' health [6]. Computer vision comes in sixth. Computer vision, an essential part of artificial intelligence, uses visual data as input to process photos and videos continuously in order to get better results faster and with higher quality than would be possible if the same job were done manually. Simply put, doctors can now diagnose their patients with diseases like cancer, diabetes, and cardiovascular disorders more quickly and at an earlier stage. Here are a few examples of real-world applications where computer vision technology is making notable strides. Mammogram images are analysed by visual systems that are intended to spot breast cancer at an early stage. Automated cell counting is another example from the real world that dramatically decreases human error and raises concerns about the accuracy of the results because they might differ greatly depending on the examiner's experience and degree of focus. A third application of computer vision in the real world is the quick and painless early-stage tumour detection enabled by artificial intelligence. Without a doubt, computer vision has the unfathomable potential to significantly enhance how healthcare is delivered. Other than for visual data analysis, clinicians can use this technology to enhance their training and skill development. Currently, Gramener is the top company offering medical facilities and research organisations computer vision solutions [7]. The usage of imperative rather than functional programming languages is one of the key difficulties in creating artificial intelligence software. As artificial intelligence starts to increase exponentially, developers employing imperative programming languages must assume that the machine is stupid and supply detailed instructions that are subject to a high level of maintenance and human error. In software with hundreds of thousands of lines of code, human error detection is challenging. Therefore, the substantial amount of ensuing maintenance may become ridiculously expensive, maintaining the high expenditures of research and development. As a result, software developers have contributed to the unreasonably high cost of medical care. Functional programming languages, on the other hand, demand that the developer use their problem-solving abilities as though the computer were a mathematician. As a result, compared to the number of lines of code needed by the programme to perform the same operation, mathematical functions are orders of magnitude shorter. In software with hundreds of thousands of lines of code, human error detection is challenging. Therefore, the substantial amount of ensuing maintenance may become ridiculously expensive, maintaining the high expenditures of research and development. As a result, software developers have contributed to the unreasonably high cost of medical care. Functional programming languages, on the other hand, demand that the developer use their problem-solving abilities as though the computer were a mathematician. As a result, compared to the number of lines of code needed by the programme to perform the same operation, mathematical functions are orders of magnitude shorter. The bulk of software developers that use functional programming languages are well-trained in mathematical logic; thus, they reason differently than most American software developers, who are more accustomed to following step-by-step instructions. The market for artificial intelligence in healthcare is expected to increase from $3.4 billion in 2021 to at least $18.7 billion by 2027, or a 30 percent annual growth rate before 2030, according to market research firm IMARC Group. The only outstanding query is whether these operational reductions will ultimately result in less expensive therapies.

Recent developments in technology have changed the learner’s profile and the learning outcomes. Today, with the emergence of higher-order thinking skills and computer literacy skills, teaching through traditional methods is likely to fail to achieve the learning outcomes. That is why; teachers and teacher candidates are expected to have computer literacy skills. Programming is the main focus of this study since it is an important part of computer literacy. The study aims to analyze mathematics education students’ skills in the process of programming and their practices of integrating it into their teaching. The participants of the study are 42 third grade students of an Elementary Mathematics Education Program of a state university in Turkey. Within the study in which theory and practice was carried out simultaneously, the participants were taught the basics of programming and the algorithms with C programming language. The teacher candidates put the theoretical knowledge into practice using the visual programming application by MIT App Inventor at the computer laboratory. In addition, they used the MIT App Inventor visual programming environment to develop programs they will use in teaching mathematics in groups. Given the component of teaching of programming during this process, it is considered that the process of teaching in question will be effective in planning the teaching process of future studies. The reason is that not only it analyses the development of the variables used in this study but also because it takes into consideration the opinions of teacher candidates.

Abstract : Education gamification has been spreading in various disciplines such as languages, computer programming, medicine, natural languages, engineering, etc. Software Engineering is our interest in this work as we saw an opportunity of contribution to enrich literature and empirical studies in this area. Traditional methods of teaching Software Engineering could significantly benefit from gamification as a complementary component in student learning outcomes. We believe we can provide our students with more effective learning environment in number of aspects including: providing enjoyable practice, immediate feedback, enhancing the sense of responsibility, enhanced engagement and performance real time tracking. In this paper, we will present our case study in adopting a computer game in software engineering course. Further, we will present the results of a course exist survey that shows the responses of 114 participating students. The analysis of the survey showed significant positive impact on number of aspects including: student engagement, learning concepts and critical thinking. The overall mean of positiveresponses was 81.2%. Keywords: Software Engineering Education, Enhancing Learning Environment, Utilizing Games in Learning.

Many studies have shown that the shift from contact teaching to fully online teaching has had many negative effects on teaching and learning during the COVID-19 pandemic. Although the pandemic has also had an effect on leading teaching in higher education institutions, there has not been much empirical research on leaders’ experiences during a pandemic. The present study brings out the voices of academic leaders themselves and how they experienced the pandemic in the light of leading teaching that is provided exclusively online. To examine the variety of degree programme directors’ experiences, open-ended questions were asked and analysed using content analysis. Seven dimensions of experiences were detected, and they represented negative, positive and neutral experiences. The present study shows that higher education leaders need more guidance, training and support to face crisis situations and develop their skills, especially to communicate effectively, but at the same time to do so collaboratively and in an informal way.

Aim/Purpose: This study seeks to understand the various ways information systems (IS) students experience introductory programming to inform IS educators on effective pedagogical approaches to teaching programming. Background: Many students who choose to major in information systems (IS), enter university with little or no experience of learning programming. Few studies have dealt with students’ learning to program in the business faculty, who do not necessarily have the computer science goal of programming. It has been shown that undergraduate IS students struggle with programming. Methodology: The qualitative approach was used in this study to determine students’ notions of learning to program and to determine their cognitive processes while learning to program in higher education. A cohort of 47 students, who were majoring in Information Systems within the Bachelor of Commerce degree programme were part of the study. Reflective journals were used to allow students to record their experiences and to study in-depth their insights and experiences of learning to program during the course. Using phenomenographic methods, categories of description that uniquely characterises the various ways IS students experience learning to program were determined. Contribution: This paper provides educators with empirical evidence on IS students’ experiences of learning to program, which play a crucial role in informing IS educators on how they can lend support and modify their pedagogical approach to teach programming to students who do not necessarily need to have the computer science goal of programming. This study contributes additional evidence that suggests more categories of description for IS students within a business degree. It provides valuable pedagogical insights for IS educators, thus contributing to the body of knowledge Findings: The findings of this study reveal six ways in which IS students’ experience the phenomenon, learning to program. These ways, referred to categories of description, formed an outcome space. Recommendations for Practitioners: Use the experiences of students identified in this study to determine approach to teaching and tasks or assessments assigned Recommendation for Researchers: Using phenomenographic methods researchers in IS or IT may determine pedagogical content knowledge in teaching specific aspects of IT or IS. Impact on Society: More business students would be able to program and improve their logical thinking and coding skills. Future Research: Implement the recommendations for practice and evaluate the students’ performance.

AbstractOnline language teaching is gaining momentum worldwide and an expanding body of research analyses online pedagogical interactions. However, few studies have explored experienced online teachers’ practices in videoconferencing particularly while giving instructions, which are key to success in task-based language teaching (Markee, 2015). Adopting multimodal (inter)action analysis (Norris, 2004, 2019) to investigate the multimodal construction of instructions in a single case study, we examine instruction-giving as a social practice demonstrated in a specific site of engagement (a synchronous online lesson recorded for research purposes). Drawing on the higher-level actions (instruction-giving fragments) we have identified elsewhere (Satar & Wigham, 2020), in this paper we analyse the lower-level actions (modes) that comprise these higher-level actions, specifically focusing on the print mode (task resource sheets, URLs, text chat, and online collaborative writing spaces) wherein certain higher-level actions become frozen. Our findings are unique in depicting the modal complexity of sharing task resources in synchronous online teaching due to semiotic misalignment and semiotic lag that precludes the establishment of a completely shared interactional space. We observe gaze shifts as the sole indicator for learners that the teacher is multitasking between different higher-level actions. Further research is needed to fully understand the interactional features of online language teaching via videoconferencing to inform teacher training policy and practice.

Purpose Rudimentary programming is an essential, transferrable, problem solving skill in many higher education (HE) programmes in academic institutions including Software Engineering, Business Information Technology, Computer Games Development, Design and Technology. The purpose of this paper is to address some of the problematic issues associated with teaching programming by the utilisation of a new novel teaching approach called games-based construction learning (GBCL) to attempt to increase motivation, engagement and learning effectiveness. An international and national trend is to introduce coding at earlier education levels resulting in upper primary education (PE) being the focus of this paper to ascertain if GBCL using Scratch to teach programming concepts is more effective at different levels of upper PE. Design/methodology/approach A large-scale empirical study introducing GBCL to teach programming concepts into 16 classes between levels 4 and 7 in PE utilising 384 children. A detailed implementation framework for GBCL using Scratch in PE was utilised to address all incorporation issues and the games constructed by the children scored utilising a game codification scheme specifically designed to address programming and design as a quantification rubric. The experiment utilised eight 1- h lessons on GBCL using Scratch. Findings The resulted in 178 games of varying levels of complexity developed. The results indicated that GBCL was an effective mechanism to teach programming concepts using Scratch at all levels of upper PE. Primary seven students scored higher in relation to the design metric of the quantification codification rubric. Research limitations/implications Under the Curriculum for Excellence (CfE) in Scotland non-traditional teaching approaches are encouraged and development of digital literacy skill is highly advocated. This has resulted in a new approach, novel approach called GBCL where children create their own games utilising an engine such as Scratch is gaining significant attention in terms of being a novel approach. Despite a plethora of similar studies associated with GBCL, it is still not as developed as games-based learning and requires further empirical studies to support the validity of the approach and resolve identified issues. Practical implications Computer programming itself can lead to a highly rewarding career in a number of sectors from games development to banking, such as cybersecurity and systems development. In the last decade, in particular due to the ubiquitous nature of technology there is an increasing international and national trend associated with teaching rudimentary programming concepts at a far younger age including secondary education and the upper PE level. Introducing programming at an earlier level is now being considered essential as the path to transfer from novice to expert programmer level in time is considered nearly a decade approximately. The introduction of GBCL interventions may yield positive results in a supplementary learning capacity in accordance with the CfE and increase the educational effectiveness of programming education in later levels of education. Originality/value This study presents a large-scale empirical evaluation of GBCL in upper PE utilising a compiled implementation framework for incorporation and a detailed game codification scheme to quantify the games produced highlighting coding constructs and design.

Education has been integrated into the globalization process supported by technological advances such as e-learning. The sustainability of the universities is one of the key points of the university survival, and they strongly depend on the number of students that can enroll in them. Thus, many of the educational institutions have had to develop their curricula based on the use new technologies. Without a doubt, virtual laboratories are the latest technology in this regard. The objective of this work is to determine which are the main institutions and research trends in relation to virtual laboratories. The methodology followed in this research was to perform a bibliometric analysis of the whole scientific production indexed in Scopus. The world’s scientific production has been analysed in the following domains: first the trend over time, types of publications and countries, second the main subjects and keywords, third main institutions and their main topics, and fourth the main journals and proceedings that publish on this topic. After that, a case study was analysed in detailed as a representative country (Spain). The most productive institution in this field, Universidad de Educación a Distancia (UNED). If the ranking is established by average citations per published paper, the first three institutions are from the USA: Massachusetts Institute of Technology (MIT), University of Washington (Seattle), and Carnegie Mellon University. The scientific categories at world level and in the case of study are similar. First, there is the field of engineering followed by computer science and above all it highlights the wide spectrum of branches of knowledge in which this topic is published, which indicates the great acceptance of this teaching methodology in all fields of education. Finally, community detection has been applied to the case study and six clusters have been found: Virtual Reality, Users, E-learning, Programming, Automatic-robotics, Computer Simulation and Engineering Education. As a main conclusion, bibliographic analysis confirms that research in virtual laboratories is a very active field, where scientific productivity has exponentially increased over recent years in tandem with universities growth. Therefore, expectations are high in this field for the near future. The possibility of virtual laboratories opens up new perspectives for higher education sustainability, where the educational policies of countries could be reoriented.

An algorithm learning tool was developed for an introductory computer science class in a specialized science and technology high school in Japan. The tool presents lessons and simple visualizations that aim to facilitate teaching and learning of fundamental algorithms. Written tests and an evaluation questionnaire were designed and implemented along with the learning tool among the participants. The tool’s effect on the learning performance of the students was examined. The differences of the two types of visualizations offered by the tool, one with more input and control options and the other with fewer options, were analyzed. Based on the evaluation questionnaire, the scales with which the tool can be assessed according to its usability and pedagogical effectiveness were identified. After using the algorithm learning tool there was an increase in the posttest scores of the students, and those who used the visualization with more input and control options had higher scores compared to those who used the one with limited options. The learning objectives used to evaluate the tool correlated with the test performance of the students. Properties comprised of learning objectives, algorithm visualization characteristics, and interface assessment are proposed to be incorporated in evaluating an algorithm learning tool for novice learners.

Learning to program is a complex and arduous process undertaken by thousands of undergraduates in the UK each year. This study examined the progress of transforming the pedagogical paradigm of an introductory programming unit from a highly controlled, reductionist 'cipher' orientation to one in which students have more freedom to explore aspects of programming more creatively. To facilitate this, certain programming concepts were introduced much earlier that had previously been the case. This was supported by an analysis of the semiotics and symbology of programming languages that showed that there was no intrinsic support for the traditional sequence of introducing programming concepts. A second dimension to the transformation involved doubling the number of assessments to emphasise the benefits of continual engagement with programming. The pedagogical transformation was to have been phased over four successive cohorts, although the fourth phase had to be delayed due to a revalidation that amalgamated three programmes into a framework. The study was planned during the second phase of the transformation. To ensure that the study did not disrupt the students’ learning experience the main focus of the research was on quantitative analyses of the work submitted by the students as part of the coursework for the unit. This work included programming portfolios and tests. In all, the work of more than 400 students completing more than a thousand portfolios and a thousand tests were analysed, providing a holistic view of waypoints in the learning process. The analyses showed that the second and third cohorts responded positively to the greater level of freedom, creating more sophisticated applications utilising a wider range of programming constructs. In the latter part of the fourth cohort a more traditional, constrained approach was used by another tutor that resulted in a narrowing of the range of programming concepts developed. The quantitative instruments were augmented by questionnaires used to gauge the students' previous experience, and initial views. Analyses of these returns showed that there appeared to be a limited relationship between a student's previous experience and the likelihood that he or she would succeed in the unit and be eligible to continue to the next stage of the undergraduate programme. The original plan was for qualitative instruments to be introduced in the final two cohorts. The re-organisation alluded to earlier restricted qualitative methods to short, semi-structured interviews during the third cohort. Within the study, certain aspects of the pedagogical transformation were considered in more depth: the development and use of a code generator and criterion-referenced assessment. These innovations were part of another dimension of the transformation of the unit, emphasising comprehension and modification equally with construction. This dimension reflects the changing nature of programming, incorporating existing code wherever possible. The analyses showed that comprehension skills developed to a greater extent within the unit compared with modification and construction. The main conclusions of the study were that the pedagogical changes had a beneficial effect on the learning of all students, including those with considerable previous experience, and those who had never written a program before.

Despite our awareness of the fascination modern humans have with the Internet, little is known about how and why colleges and universities create and maintain Websites. At the most general level, in this case study, I hypothesize that university Websites serve as communication and marketing tools in attracting students. At the most specific level, I postulate that civil engineering programs with Web pages depicting images of women and minorities would be more successful in recruiting and retaining women and students of color than civil engineering programs with Web pages displaying fewer or no images of women and minorities. The primary goal of this case study was to examine the relationships between Website information content and the recruitment and retention of women and minority pre-civil engineering students. The second, but equally important, goal was to investigate the reason(s) why, despite efforts to recruit and retain individuals from disenfranchised populations into STEM majors, students from these groups not only remain underrepresented in engineering, but leave this discipline at a much higher rate than their non-minority male counterparts. This case study focused on two Florida state university civil engineering programs and drew on ethnographic research methods. I used interviews, focus groups, Web pages, demographic sheets, and observations to examine the relationships between Website content and access to undergraduate civil engineering programs for women and students of color. The study sample involved 40 respondents, including pre-civil engineering students, civil engineering professors, and university administrators. Research findings suggested that Internet marketing has become a key strategy used by civil engineering programs in recruiting and retaining students from underrepresented groups. Additionally, the study revealed that both prospective and pre-civil engineering students use departmental Websites for communication and enrollment purposes. Last, but certainly not least, the study found that online climate is a significant factor in the recruitment and retention of women and students of color in civil engineering programs.

The contemporary classroom currently faces an evolving world of computer based training, online courses, instructor-led learning and several blended approaches in-between. With the increased presence of computers and communication in every facet of students' lives, students have changed to adapt to the continuous presence of technology in their daily lives. These recent rapid developments have changed the relationship between technology and communication. Indeed, communication and technology have become linked to such a degree that it is difficult to differentiate one from the other, thereby altering our rhetorical situation as instructors. Instructors can no longer deny the presence of technology in the contemporary classroom, much less in the contemporary composition classroom. This case study serves as a post-modern analysis of the technology based blended classroom. A gap exists between what online learning is (being) today and what it is (becoming) tomorrow. This dissertation explores the gap by examining two rich data sources: online visitor navigational patterns and instructor interviews. The fundamental ideas that this text explores are the following: - Web server logs and PHP logs can be analyzed to yield relevant information that assists in the design, architecture, and administration of online and blended learning courses. - Technology in the writing classroom does not necessarily solve traditional problems associated with the composition classroom. Technology is a tool, not a solution. - Technology has changed the rhetorical situation of the composition classroom. As a result, instructors must adapt to the changed rhetorical environment. Via this study, readers will hopefully gain a better understanding of the relatively unexplored margins between instruction, composition and technology paradigms. Instructors, trainers, technical writers, pedagogues, industry and academia alike must step forward to research technology-assisted pedagogy so that they can de-privilege the paradigms that position technology itself as a solution, and move forward toward realistic and real-world expectations for instructors in technology mediated learning environments.

The evolution of technologies used for learning in open distance learning (ODL) has compelled academics to upgrade their teaching skills and competencies in order to teach in an ever-changing environment. While the earlier ODL generations were characterised by the use of written, printed texts, radio, television, print media and postal services, the current generations are characterised by the use of information and communication technologies (ICT) to enhance teaching and learning. This study explored the experiences of academics who participated in the staff development courses for innovative teaching and learning at the University of South Africa. To explore the experiences, a qualitative research design of a phenomenological genre was adopted. Using interviews, data was collected from six purposively selected academics and analysed following Giorgi’s phenomenological methods. The academics’ experiences and concerns provided some insight into their development needs and how they would have liked to have been developed for innovative teaching. It emerged that staff development provided valuable knowledge, skills and competencies, enabling and promoting innovative forms of e-teaching and learning. These experiences and concerns were synthesised into a staff development framework consisting of four phases: Orientation; Learning; Acquisition of skills and Competencies; and Performance indicating that effective staff development requires that participants are initially orientated to the training programme before exposure to authentic learning activities. Through this exposure they acquire the vital online teaching skills and competencies thereby enhancing their performance as online teachers. The staff development framework indicated further that for effective staff development to take place, the different phases should not only be supported by university management but also by an evaluation mechanism to establish whether the objectives in each phase have been achieved. It also emerged that time played an important role in staff development, as the duration of each phase and the development intervention as a whole affects how well academics are able to acquire and perfect their teaching skills.
Curriculum and Instructional Studies
D. Ed. (Curriculum Studies)

The research aimed to assess the feasibility of using podcasts in mobile devices to teach research proposal writing for masters’ students of University of South Africa. To aid in this, a general objective was developed which was supported by specific research objectives that guided the study. The research looked at the evolution of open distance learning (ODL) including the use of M-learning. I reviewed literature on the history of podcasts as an entertainment tool being highlighted as a revolution in the academic world especially in the area of distance learning. To create a foundation to give strength to the use of podcasts, theories of education were evaluated and criticised to give reason and foundation for the use of podcasts as a technology to support teaching and learning in ODL. All major aspects of learning were traversed in the theoretical aspect. This is in a bid to assess the ability of the use of podcasts to meet the needs of the learners. A methodology for conducting the research that included the deployment of a pilot project for the research proposal writing module in year 2011-2012 class was developed and justified accordingly. The use of both qualitative and quantitative methods was necessitated by the objectives of the research. This was implemented at data collection and analysis stages of the research. The analysis was fruitful and successful for that matter, giving reasonable backing to the proposal by the researcher of adopting the use of podcasts using mobile devices. The analysis deemed the pilot project successful for the period within which it was operated. Hurdles or challenges were present and the study gives them as majorly, the lack of sufficient skills to handle the content of the website, that is, generally, the use of the technology. Also, the study pinpoints that the availability of mobile devices is also a challenge that the students will face. Recommendations were derived from the challenges and include a framework that should be used in creating a podcast support system that will be based on the findings to create a successful project. Regarding the objectives of the study, the conclusion that indeed it is feasible to use podcasts to teach research proposal writing in Unisa is valid.
Curriculum and Instructional Studies
D. Ed. (Didactics)

Most of Finland’s landmass consists of vast, sparsely populated rural areas. Even though there are high school students in these areas who are interested in Computer Science (CS), and especially in programming, the educational institutions that they attend in these rural areas cannot offer them more advanced levels of CS studies. To meet this need, the Department of Computer Science of the University of Joensuu, Finland, has devised for such students an e-learning program called ViSCoS (Virtual Studies of Computer Science). This program enables ViSCoS students to study first-year university-level Computer Science courses through the medium of the Web. A total of 109 students completed the ViSCoS program between the years 2000-2005. The designers of the program concomitantly created a number of digital learning environments that supports ViSCoS learning and teaching activities. The FOrmative DEvelopment Method (FODEM), an action research-oriented design method used in the ViSCoS program, has enabled gradual development in the program.

The COVID-19 pandemic has affected all sectors of society, including higher education. To mitigate the spread of SARS-CoV-2 and protect employees and students, the Portuguese government has decreed mandatory closure in all sectors. In this scenario, higher education institutions were forced to transform face-to-face education into a mix of face-to-face and virtual education. This chapter intends to share information for teachers and students who want to swiftly implement an emergency hybrid education model. Based on the author's experience, studies of data collected before and during the pandemic, and observations of the students' adaptation process in this swift transition from face-to-face teaching to the emergency hybrid teaching model dictated by a polytechnic institute in Portugal, in a curricular unit whose focus is to teach algorithms, computer programming, and data structures, trained in an engineering course, it was possible to identify a set of extrinsic and intrinsic factors to consider in case of similar crisis situations or others that may arise.

Asynchronous web based instruction, more commonly known as online education or distance learning, has been available for some time. This technology has brought education within the reach of many who would otherwise be unable to attend live classes. Time schedules and distance no longer have a bearing on attending a course. Even group projects are manageable with email and discussion groups. Many courses convert quite well to the online format, and studies have shown that students can learn as much from online courses as from live courses. In many cases, multiple course certificate programs and even some complete degree programs are offered online. As inviting as online courses may be, they do have their limitations, especially classes with a laboratory component. A number of institutions have offered laboratory-based classes in an online format with varying degrees of complexity and success. In some cases, students travel to the institution a limited number of times for extensive laboratory experiences while other institutions use what might best be described as virtual reality based systems. This paper discusses Purdue University Calumet’s first laboratory-based online course, MFET 275, Computer Numerical Control Programming Application. A combination of technologies makes this course successful and effective. Development procedures for this course along with technology used, online pedagogy issues, and course assessment are covered in this paper. Suggestions for future course development complete the discussion.

[The final form of this paper was published in the journal Issues in Informing Science and Information Technology.] An algorithm learning tool was developed for an introductory computer science class in a specialized science and technology high school in Japan. The tool presents lessons and simple visualizations that aim to facilitate teaching and learning of fundamental algorithms. Written tests and an evaluation questionnaire were designed and implemented along with the learning tool among the participants. The tool’s effect on the learning performance of the students was examined. The differences of the two types of visualizations offered by the tool, one more input and control options and the other with fewer options were analyzed. Based on the evaluation questionnaire, the scales with which the tool can be assessed according to its usability and pedagogical effectiveness were identified. After using the algorithm learning tool, there was an increase in the posttest scores of the students and those who used the visualization with more input options has higher scores compared to those who used the one with limited input options. The learning objectives used to evaluate the tool correlated with the test performance of the students. Properties comprised of learning objectives, algorithm visualization characteristics and interface assessment are proposed to be incorporated in evaluating an algorithm learning tool for novice learners.

Digital literacy has become more and more important in the last decade, and many people predict that in the future, the need for digital skills will be even more crucial than it is today. The dynamic development and use of technology are becoming increasingly common in all areas of life, changing demands of modern life and the labor market, which makes it necessary to educate students from many different study-programs on how to use different digital tools and how to program. Depending on different professions, there are different requirements on what it means to have digital literacy. For some it is most important to know how technologies are created or to use the product effectively, for others it is the security of data transfer that is essential. The different professions have different needs for digital literacy and different use for programming skills. Teaching computer programming can be particularly difficult in the case of introducing programming for non-computer scientists. While computer science itself (programming) is relatively well described in the subject’s literature, the use of programming in other professions is not well defined. There are different suggestions, recommendations according to the level of education (primary, secondary, higher) or the study-programs the students take. There is no definition of what digital literacy is in different professions, what it means to know computer programming in different professions, and to what extend the students from non-computer science courses should master digital literacy and programming. That can cause challenges for the teachers and students in non-computer science professions that are required to know computer programming for their future jobs. There is no doubt that academic computer science skills for non-programmers can mean/contain different knowledge depending on course curriculum, teachers' experience, chosen literature, but the level of obtaining digital skills should be comparable, adequate, and relevant for the modern citizen. This article presents requirements, some descriptions/cases of introduction to programming for non-computer scientists from a teacher’s perspective. An adaptation of the general programming knowledge into the specific need of different subjects. The data is collected from higher education teachers that have different backgrounds and are teaching at different study-programs to get various views and experiences. The analysis of the findings uses SOLO-taxonomy to compare to what extend the different courses introduce programming to students.