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This study focuses on how to teach basics of machine learning (ML) in K-12 settings. Since ML can be considered as a vital part of future computational skills, it is justified to be included as part of the computational thinking teaching agenda in K-12 level. The outcome of the study will help to understand the existing system in teaching ML and its algorithm, identify strategies and pedagogical frameworks for teaching ML in K-12 education. The research outcome will further motivate young learners to learn and practice machine learning algorithm and as well encourage/build teachers’ capacity in teaching ML.
Team
Prof. Markku Tukiainen, Dr. Jarkko Suhonen, Dr. Solomon Oyelere, Dr. Henriikka Vartiainen
Large-scale land deals are among the most challenging development issues of today. They have attracted considerable attention for various reasons, including their implications for environmental justice and changes in local livelihoods. This phenomenon, also known as "land grabbing," is a significant driver of environmental change globally and, locally, it prompts a substantial reconfiguration of access to land and land-based social relations. While proponents frame the phenomena as a development opportunity, encompassing improvement in the livelihoods of local people, opponents counter-frame it as an impoverishing scheme. In Ethiopia, which is a primary target for large-scale land acquisitions, land is a major resource for state control and foreign direct investment. As the foundation of their livelihoods and anchor of their identity, it is simultaneously a vital resource for the local people. Many studies have indicated the adverse consequences of large-scale land transfers in terms of both procedural imperatives and outcome indicators. However, there is limited research that compares its processes and outcomes among countries characterized by different political histories, land policies, and state-society relations. In order to address this knowledge gap, this study attempts to answer questions of procedural justice (process) and distributive justice (outcome). Procedural justice is operationalized through the concepts of recognition, representation, and participation, whereas distributive justice relates to the (re)distribution of environmental benefits and burdens among stakeholders. The study applies a political-ecological approach as the overarching theoretical framework, complemented by analytical insights derived from recent advances in environmental justice conceptualizations. Methodologically, it will adopt a mixed-methods approach, involving the combination of quantitative and qualitative methods for data collection and analysis. Based on empirical evidence and contextualizing the local livelihood dynamics within broader structural and political-economic conditions, this study contributes to the ongoing debate on livelihood impacts and environmental justice implications of transnational land acquisitions.
Team
This study focuses on the effect of electronic invoicing on the society. Direct emissions is a big challenge in Africa and to reduce it should be the priority of the government and the policy makers. The outcome of the study will help the African community to learn from the green strategy of the advanced countries such as Finland.
Team
Ismaila Sanusi Alex Dada