Should touch screen tablets be used to improve educational outcomes in primary school children in developing countries?

The 2030 Agenda for Sustainable Development aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” (United Nations, 2015). Whereas, the principal focus of global education planning since 2000 had been on getting children into schools, sustainable development goal 4 (above) reflects concerns about quality. As improving learning outcomes starts to receive heightened policy focus, it becomes imperative to consider the types of intervention that can be most effective in raising learning outcomes, particularly in settings characterized by poor resourcing and persistent low attainment levels. Here, we consider if touch screen tablets can be used to improve educational outcomes in primary school children in developing countries. We focus on early maths attainment in Malawi as one of the most dramatic examples of the current learning challenge

Creativity-Supporting Learning Environments : Two Case Studies on Teaching Programming

It is known that students' learning approaches, types of motivation, and types of self-regulation are connected with learning outcomes. It is also known, that deep learning approaches, self-regulated learning, and intrinsic types of motivation are connected with creativity. However, in computing pedagogy there is a lack in empirically grounded analyses in integration of the varying educational theories to build learning environments that support creativity. The literature of programming education proposes a variety of theoretical, as well as practical viewpoints in relation to the teaching and learning situation. However, little effort has been put on understanding cultural and contextual differences in pedagogy of programming. Literature shows that education is highly context dependent, and that educational design should account for contextual differences. In programming education, the nature and implications of those differences are hitherto unclear. In this study, the paucity in research about creativity-supporting learning environments in computing education, and about contextual differences in the pedagogy of programming are addressed through two case studies. In the first context (CUH) of this study (Department of Computer Science, University of Helsinki, Finland), a method of learning-by-inventing was designed and integrated into a robotics-based programming class, and its effects on students' learning were investigated through qualitative analysis of 144 interviews. In the second context (CTU) of this study (IT Department, Tumaini University, Iringa University College, Iringa, Tanzania) a number of interventions for supporting intrinsic motivation and deep approaches to learning were designed, and their effects on students' learning were studied through qualitative and quantitative methods, and a controlled research setup. In addition, a mixed methods study about contextual factors, which affect the learning environment design was conducted. In context CUH, the results show that the provided environment supported the learning of creative processes through a number of mechanisms. In general, the provided environment was shown to facilitate changes in students' problem management approaches, and extended students' deep and surface learning approaches to computer science related problem solving and problem management. In context CTU the results reveal that students face many similar challenges than students in other educational contexts, and that the standard learning environment does not offer enough support for gaining the requisite development. Learning is also hindered by many contextually unique factors. Testing a model where students work on their homework under guidance, facilitated by active student-teacher collaboration did not result in significant advantage over the control group. However, the qualitative results about guided environments were exclusively positive. In context CUH, the analysis suggests that learning of creativity may be facilitated by supporting deep learning strategies, intrinsic motivation, and self-regulated learning through utilizing a combination of open learning environment configuration, learning-by-inventing, and robotics as the vehicle for learning. Secondly, the analysis suggests challenges in context CTU to be addressed through increasing the number of practical exercises, by selecting the proper amount of guidance required in the learning environment, and by implementing educational action research as a standard component into the learning and teaching environment.Tässä viiteen artikkeliin perustuvassa väitöskirjassa tutkittiin keksimisen ja luovan ongelmanratkaisun tukemiseen perustuvia uusia opetusjärjestelyitä kahdessa kontekstissa: 1) Helsingin yliopiston Tietojenkäsittelytieteen laitos, sekä 2) IT-Department, Tumaini University, Iringa University College, Iringa, Tansania. Ensimmäisessä kontekstissa hyödynnettiin robotiikkasarjaa oppimisvälineenä. Ensimmäisessä kontekstissa tulokset osoittavat, että tutkimuksen osana suunnitellut opetusjärjestelyt tukivat syvällisempiin opiskelutapoihin suuntautuneita muutoksia opiskelijoiden ongelmanratkaistavoissa-, ongelmien löytämistavoissa, ja ongelmajoukkojen hallintatavoissa. Tutkimuksen toisessa kontekstissa tulokset osoittavat, että opiskelijat kohtaavat useita samankaltaisia oppimisen haasteita kuin muissakin konteksteissa. Oppimiseen vaikuttaa myös joukko kontekstiin liittyviä uniikkeja tekijöitä. Tulosten analyysi osoittaa, että tutkimuksen ensimmäisessä kontekstissa keksimisen oppimista voidaan tukea hyödyntämällä avoimen oppimisympäristön periaatteita, ja robotiikkasarjaa oppimisen alustana. Tulosten analyysi osoittaa myös, että tutkimuksen toisen kontekstin haasteita voidaan ratkaista lisäämällä käytännön harjoitusten määrää ja laatua, valitsemalla oikeanlaiset oppimisen tukitoimet, sekä liittämällä opettamisen ja oppimisen tutkimus olennaiseksi osaksi opetustoimintaa

Towards a Creator Mindset for Computational Thinking: Reflections on Task-Cards

Computational thinking (CT) skills are nowadays strongly advocated for educational institutions at all levels. CT refers broadly to skills of thinking about the world from a computational perspective, however, not necessarily referring to programming skills in particular. There is still a lack of consensus about what CT means, and how CT should be taught. This open peer commentary briefly discusses some ongoing trends of CT in response to the target article, which reports development, field testing and piloting of an extensive set of new learning materials for teaching CT. Recent calls for interdisciplinary technology education, creativity and open-ended problem solving in CT are highlighted.</p

Mobile Technology Usage for Street Traders’ Market Search in Dodoma—Urban Tanzania: An Exploratory Study

Increased access to mobile technologies has significantly contributed to almost all types of work, including informal work. Mobile phones are one such technology that has been exponentially adopted and used by street traders. However, there is limited information about how street traders use mobile phones to search for new markets. This study investigated street traders’ mobile usage for new market search in Dodoma, Tanzania. Qualitative data were collected using in-depth interviews with 29 street traders, followed by a focus group discussion with eight street traders. Thematic analysis was used to analyze the data. The results show that using mobile phones to search for new markets is scarcely practiced due to certain challenges, such as high costs, technical problems, misuse of mobile contacts by customers, and a concentration of similar products in one location. The findings call for a reduction of mobile service costs, improvement of mobile infrastructure, and provision of education to street traders and customers so that they learn how to use mobile phones for business communication more effectively as well as to abide by communication ethics

First Year CS Students Exploring And Identifying Biases and Social Injustices in Text-to-Image Generative AI

Conference Contribution, Faculty of Economic and Management Sciences (Research & Innovation)--Northwest University, Vanderbijlpark CampusGenerative AI is a recent breakthrough in AI. While it has become a hot topic in computing education research (CER), much of the recent research has focused on e.g. issues of plagiarism or academic integrity. One problem spot with Generative AI is its susceptibility to various kinds of algorithmic bias. In this study, we collected data from an introductory computing course, where students experimented with text-to-image generative models and reflected on their generated image sets, in terms of biases, related harms, and possible fixes. Data were collected in Fall 2023 (pilot data in Fall 2022). Data included reports from 163 students. The results show (1) a variety of bias types observed by students related to gender, ethnicity, age, as well as a variety of bias types not observed by students, (2) two major types of attributions for the source of bias: bias caused by biases in the society and bias caused by data or algorithms, and (3) a number of potential harms associated with the biases, as well as attributions of those harms in specific contexts and use cases

Computing education research in schools

One of the most researched domains of computing education research (CER) that attracts attention is computing education in schools, starting from pre-primary level up to upper secondary level (K-12). A high number of initiatives and related research contributions have appeared over half a century of computing history in schools. This chapter presents an overview of CER in the K-12 domain, including globally influential movements such as that of Logo pedagogy, constructionism, inquiry based learning or computational thinking (CT). Development of CT in education, based on a number of previous reviews on CT and K-12, paints a diverse picture of the approaches, educational technologies, pedagogical innovations, and related challenges such as lack of teacher training or shortage of learning resources. This article presents also a scientometric overview of CER research in the K-12 domain. The analysis identifies the top topics of research, and foundational articles. While much of the research is centered around the US, key research from other parts of the globe is also highlighted. Emergence of new trends such as teaching artificial intelligence and machine learning in schools are also discussed.</p

Computing education research in schools

One of the most researched domains of computing education research (CER) that attracts attention is computing education in schools, starting from pre-primary level up to upper secondary level (K-12). A high number of initiatives and related research contributions have appeared over half a century of computing history in schools. This chapter presents an overview of CER in the K-12 domain, including globally influential movements such as that of Logo pedagogy, constructionism, inquiry based learning or computational thinking (CT). Development of CT in education, based on a number of previous reviews on CT and K-12, paints a diverse picture of the approaches, educational technologies, pedagogical innovations, and related challenges such as lack of teacher training or shortage of learning resources. This article presents also a scientometric overview of CER research in the K-12 domain. The analysis identifies the top topics of research, and foundational articles. While much of the research is centered around the US, key research from other parts of the globe is also highlighted. Emergence of new trends such as teaching artificial intelligence and machine learning in schools are also discussed.</p

Mobile Technology Usage for Street Traders’ Market Search in Dodoma—Urban Tanzania: An Exploratory Study

Increased access to mobile technologies has significantly contributed to almost all types of work, including informal work. Mobile phones are one such technology that has been exponentially adopted and used by street traders. However, there is limited information about how street traders use mobile phones to search for new markets. This study investigated street traders’ mobile usage for new market search in Dodoma, Tanzania. Qualitative data were collected using in-depth interviews with 29 street traders, followed by a focus group discussion with eight street traders. Thematic analysis was used to analyze the data. The results show that using mobile phones to search for new markets is scarcely practiced due to certain challenges, such as high costs, technical problems, misuse of mobile contacts by customers, and a concentration of similar products in one location. The findings call for a reduction of mobile service costs, improvement of mobile infrastructure, and provision of education to street traders and customers so that they learn how to use mobile phones for business communication more effectively as well as to abide by communication ethics.</div