Tag: Education

Finland’s Education Model – What Makes It One Of The Best In The World

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Reading time: 5 minutes

Finland has ranked high in many international education rankings and has the reputation of having one of the best education systems. But why does this country stand out from the rest, what makes it so unique and how can we learn from their method so that we can also improve. 

Finnish students consistently perform well in PISA (Programme for International Student Assessment) rankings, often placing at or near the top in reading, science, and math. Finland’s education system was reformed in the 1960s and 1970s to promote equality and economic recovery after the country’s wars. Teachers’ training and the shift from an elite system to one with comprehensive schools for all children have been key to the country’s success. This journey began in the 1960s, when Finland transitioned from sorting students into academic and vocational tracks to creating a comprehensive 9-year school system in 1972. This included reforms to teacher education, moving it from training colleges to universities and making a master’s degree a prerequisite by 1979. The reform gave teachers more autonomy and responsibility, culminating in the profession gaining prestige in the 1990s. 

Decentralization in 1985 gave more power to municipalities, and the national core curriculum in 1994 allowed local schools to design their own curriculum. Teacher autonomy and decentralization took time to develop, with a gradual shift over about two decades. Finland’s success in education, therefore, was built on a long and steady process of reform and gradual shifts in policy, structure, and perception.  
Let’s dive into the most important factors that differentiate the Finish system from the rest. 

The Finnish Method

No Standardized Testing 

Finland doesn’t rely on standardized tests for assessing students. The only exception is the voluntary National Matriculation Exam at the end of upper-secondary school (similar to high school). Students are graded individually by their teachers, and progress is tracked by the Ministry of Education through sampling across schools. 

Teacher Accountability 

Finnish teachers are highly trusted professionals, selected from the top 10% of graduates. They are required to earn a master’s degree and given the freedom to decide the best approach for teaching. Teachers collaborate and are supported by special educators like social workers, psychologists, and nurses. The system emphasizes “whatever it takes” to help students succeed, even for those with learning difficulties or behavioral issues. 

Cooperation Over Competition 

Finland’s educational philosophy strives for cooperation rather than competition. There are no rankings for top schools or teachers. The focus is on creating a cooperative learning environment that benefits everyone, rather than promoting competition. 

Focus on Basic Needs 

Finland prioritizes social equity, providing free meals, healthcare, psychological counseling, and individualized guidance for students. Education is seen as a tool to reduce social inequality and foster equality. 

Late Start to School 

Finnish children begin school at age seven, allowing them a more relaxed early childhood. Compulsory schooling lasts for nine years, and after age 16, further education is optional. This helps students avoid feeling trapped by the school system. 

Post-School Options 

Finland offers students choices beyond a traditional university route, such as vocational education programs. Students can choose between a university preparation track or a vocational path, both leading to professional careers. 

Later Start Times and Shorter School Days  

Finnish students start school later, around 9:00-9:45 AM, and finish by 2:00-2:45 PM. Research shows that later start times are beneficial for students’ well-being. Schools are structured to focus on holistic learning, with longer breaks and fewer hours of class. 

Consistent Teacher-Student Relationships 

In Finland, students often have the same teacher for multiple years, creating a strong bond and trust between teachers and students. This consistency helps teachers better understand individual student needs. 

Relaxed Learning Environment 

Finnish schools advocate for less stress and more relaxation. Students have fewer classes and enjoy multiple breaks throughout the day to stretch and socialize. Teachers also benefit from dedicated time to relax and prepare.  

Minimal Homework 

Finnish students spend less time on homework compared to students in other countries, averaging just 30 minutes a night. With less outside work, students can focus more on learning without the added pressure of extensive homework. 

Focus on Equality and Inclusivity 

They promote equality, aiming to offer the same quality of education to all students, regardless of their background. Over 30% of Finnish children receive special help, and schools are well-equipped to support children with diverse needs, including immigrants. The goal is to mainstream all students and address their individual learning needs. 

Supportive Government Policies 

The Finnish government supports families through generous maternity leave, subsidized daycare, free student health care, and public preschool, ensuring all children, even from low-income families, have access to education. 

Critiques of this system 

Finland’s exceptional performance in PISA assessments (2000) impressed many, with a unique education system that emphasized less teacher-centric, pupil-led learning. However, its scores have declined in subsequent assessments, raising questions about what went wrong. 

Declining PISA Scores: Finland now scores below average among OECD countries, with various reasons suggested for this decline. Commonly cited factors include: 

  • Over-digitalization: Excessive use of technology, particularly tablets and laptops, has been linked to lower reading scores, especially among boys, and negatively affected physical activity and sleep schedules. 
  • Mental Health Issues: A decline in student mental health is considered a contributing factor. 
  • Family Social Background: The growing influence of family background on student performance, especially in immigrant communities, has exacerbated inequalities. 
  • Gifted Students: The system struggles to adequately challenge gifted students, which contrasts with systems in countries like those in Asia, where all students are expected to meet the same standards. 

Gender Gap: Finnish boys consistently underperform compared to girls, particularly in reading. This gender gap is one of the highest among the 74 PISA countries. 

Budget Cuts: After the 2008 financial crisis, cuts to education budgets have led to teacher shortages, particularly in special education, affecting children with autism and special needs. These cuts have also deepened disparities linked to social and immigrant backgrounds. 

Social Issues: Immigrant students face difficulties such as racism, lack of support, and a struggle to integrate into society. They also have the lowest reading scores in OECD (Organisation for Economic Co-operation and Development) countries. 

Teacher Roles and Structural Problems: Finland’s highly respected teaching profession has become increasingly bureaucratic, shifting teachers’ focus away from instruction to non-teaching tasks. This shift, combined with the pupil-led approach, may have contributed to the decline in PISA scores. 

Over-digitalization and Its Consequences: The rush to incorporate technology in education, such as giving first graders iPads, has raised concerns. The excessive screen time, especially without filters or limits, has contributed to poorer sleep and concentration, which in turn has affected academic performance. 

Structural and Policy Recommendations: The article suggests that Finland should address issues such as the gender gap, budget cuts, social inequality, and over-digitalization. Increased cultural awareness and better support for disadvantaged students, along with addressing special education shortages, could help improve the system. 

Conclusion 

All in all, Finland’s education system stands as a global benchmark for its focus on equality, teacher professionalism, and holistic student well-being. While the country has experienced impressive success over the years, recent challenges, such as declining PISA scores, over-digitalization, and rising inequalities, highlight the need for ongoing adaptation. To sustain its position as a leader in education, Finland must address these emerging issues by refining its approach to technology, mental health, and inclusivity. By continuing to prioritize cooperation, individualized support, and educational equity, Finland can maintain its reputation as a model for nations striving to create more effective and fair education systems. 

Sources:
https://blogs.worldbank.org/en/education/finland-s-education-system-journey-success

https://www.smithsonianmag.com/innovation/why-are-finlands-schools-successful-49859555/

https://worldpopulationreview.com/country-rankings/pisa-scores-by-country

https://www.weforum.org/stories/2018/09/10-reasons-why-finlands-education-system-is-the-best-in-the-world/

https://bigthink.com/the-present/finland-education-system-criticisms/

Teresa Catita 

Research Team Member & Editor

AI, The Good, The Bad and The Ugly 

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Reading time: 12 minutes

The Intellectual and Environmental Ethics of Artificial Intelligence 

For the past years, artificial intelligence (AI) has had a rather prevalent impact on our lives: from assembling cars to determining which ads one is exposed to on social media. However, the emergence of generative AI, as a new category of technological resources, has taken the world by storm, with OpenAI’s ChatGPT alone reaching 300 million weekly active users in December 2024 (Singh, 2025) and, thus, having major implications not only on the environment but also on the unique human ability to envision and create. According to Gartner, AI-driven data analysis is set to account for more than 50% of all business analytics by 2025, while Forbes reports that AI-powered advertising tools can increase ROI by up to 30% compared to traditional methods.  

In fact, as you read this sentence, generative AI programs may already be developing email prompts, debugging your code, and even preparing your dinner’s recipe simultaneously.  

With the of AI usage re-shaping the way one works and interacts, as well as the possible rise of DeepSeek, which is projected to surpass ChatGPT’s performance, (Wiggers, 2025) clear benefits are defined, as studies predict 40% productivity improvements (MIT Sloan, 2023). Nevertheless, its groundbreaking promise to improve performance has been tempered, as of late, with growing concerns that these intricate and mystifying systems may do more societal harm than economic good, namely regarding creative outlooks and academic integrity (UNESCO, n.d). 

As people progressively feel the immense rush of having more and more automated activities in their lives while companies hurry to improve efficiency, one should stop to think and ask: 

What are the trade-offs for such benefits?

Intellectual Property

“And your novel?” 
“Oh, I put in my hand and rummage in the bran pie.” 
“That’s so wonderful. And it’s all different.” 
“Yes, I’m 20 people.” 

– Virginia Woolf and Lytton Strachey

 Retrieved from In the Margins: On the Pleasures of Reading and Writing 

Creation is a complex and often unappreciated place, where the creative must give shape to wild, wanderer, unstructured ideas – many times, rummaging in the bran pie to see what comes out – to form a cohesive original piece. The realization that this type of work must be protected, so as to justify its high stakes, gave birth to the concept of intellectual property.  

According to the World Intellectual Property Organization (WIPO), intellectual property (IP) refers to “creations of the mind, such as inventions; literary and artistic works; designs; and symbols, names and images used in commerce”. IP is protected by law: the Intellectual Property Rights (IPR), which encompass the right to be credited for their own work; to uphold their integrity; for others not to use the artists’ work without permission… Generative AI comes to challenge those pre-established rules.  

By giving birth to unseen imagery with the utilization of prompts, creating adapted screenplays set up on the scenery of your favorite novels, and even developing catchy songs about the dean of your school – always surprisingly fast –, AI is increasingly taking its place at the creatives’ desk. But there is a catch: GenAI does not materialize exactly original elements. Rather, the tools are based on massive amounts of data, which are used to train them into recovering patterns that then enable the response to the prompt (MIT Sloan 2021).  

This can become problematic when one starts to ask if there is ownership of the content that is provided to train Generative AI. This matter has already been brough up in the courtrooms. For example, Andersen v. Stability AI et al., in 2022. Various artists filed a class-action copyright infringement lawsuit against several AI organizations, claiming unauthorized use of their work for AI training (Harvard Business Review 2023). Ultimately, the courts’ decisions are going to add to the interpretation of the fair use doctrine.   

Artists around the world are also starting to take the matter into their own hands. One of the most impactful cases of such traces back to the Writers Guild of America strike, that marked 2023. The culmination of this event consisted of an agreement which, among other things, laid ground for the establishment of artificial intelligence use. Although artists may use AI tools in their work, companies are prohibited from forcing them to do so – which would probably result in the drafting of lower paying contracts. More importantly, now “the WGA reserves the right to assert that exploitation of writers’ material to train AI is prohibited by MBA or other law” (Vox 2023). 

AI’s Role in Academic Integrity 

One has to be honest in one’s work, acknowledge others’ work properly, and give credit where one has used other people’s ideas or data.”  

– Campbell & Waddington, 2024 

Academic integrity is a critical component in education and research work within today’s rapidly evolving academic landscape as it reflects the value of the qualifications offered by an institute, as well as the ethical conduct of students. It regards the collective activity of students and teachers to demonstrate courtesy toward intellectual property and uphold moral and ethical standards in academic works. According to the European Network for Academic Integrity (ENAI), this concept includes “compliance with ethical and professional principles, standards, practices and consistent system of values that serves as guidance for making decisions and taking action in education, research, and scholarship.”. 

With the growing presence of generative AI, students and academic researchers are supported in various aspects, including data analysis, decision-making and writing. AI has, in this sense, revolutionized the academic world, offering unmatched assistance. Nevertheless, its rapid integration into the sector, as well as its inability to understand and produce authentic scholarly work, raises concerns on students’ critical thinking capacities, plagiarism and overall academic integrity.   

In fact, a study conducted with a sample of 5894 students across Swedish universities highlights a growing dependency on AI tools, with over 50% of positive responses to the use of chatbots, and over a third of students affirming the regular reliance on Large Language Models (LLM), such as ChatGPT in education (Malmström et al. 2023). As AI tools are becoming progressively user-friendly, barriers to its wide adoption are significantly reduced. Namely, ChatGPT and similar AI applications can serve as self-learning tools, assisting students in acquiring information, answering questions and resolving problems instantaneously, thereby enriching learning experiences and offering personalized support.  

However, despite its potential to enhance academic work, people’s perceptions around its misuse for academic shortcuts still indicate mixed responses (Schei et al. 2024). The debate further extends to ethical territory, as AI-facilitated plagiarism and academic misconduct becomes increasingly prevalent and possibly encourages a culture of intellectual laziness and plagiarism practices, such as Mosaic Plagiarism: which involves taking phrases from a source without crediting them or copying another person’s ideas and replacing these with synonymic phrase structures but for proper crediting (Farazouli et al. 2023). 

Data sets used by LLMs often rely on information collected through data scraping from third-party websites and published work. While this practice is not necessarily considered misconduct, it may be obtained without explicit consent from the sources, meaning that it is possible for one’s AI-generated work or writing material to contain non-credited phrases and ideas. One example of such occurrence lies within the lawsuit infringed upon Open AI by the New York Times for copyright issues and unauthorized use of published content to train AI models (The New York Times 2023). Furthermore, critics also point out generative AI’s technical limitations and existing bias dependent on its training data, as it may create incorrect or outdated information, leading to extended reliability concerns.  
As AI becomes more deeply integrated in academia, without proper education, its misuse and over-reliance are a prominent motive for concern. 

Environmental Impact and Water Consumption  

Another factor to account for when addressing AI usage and reliance is its environmental impact, which is not often considered by end-users.  

As worldwide corporate AI investments experienced exponential growth in the past years, from $12.75B in 2015 to $91.9B in 2022 (Statista 2024), so does its impact on water consumption since AI models (especially GPT-4) require significant energy and water resources to its function. 

Global total corporate AI investment from 2015 to 2022 – Statista 

When assessing water consumption in data centers, one should account for both its “onsite” direct use to cool servers, and its indirect use as an energy generator.  (OECD.AI n.d.) 

Furthermore, the data centers require the use of fresh water for refrigeration through cooling towers, liquid cooling, or air conditioning, while power plants supplying electricity also need large amounts of water. Thus, training and running AI models can consume millions of liters with even small AI questioning using significant amounts, as these consume 1.8 to 12 liters of water per kWh of energy.  

AI’s water usage is, thereby, a growing concern, its growing water demands outpacing energy efficiency and being projected to reach up to 6.6B cubic meters (approximately 6 times of Denmark’s annual water withdrawal) (Li et al. 2025). 

The hazard that AI imposes on the environment goes far beyond the hydrological issue discussed. 

In a study carried out by Strubell et al. (2020), it was demonstrated that the carbon dioxide emissions associated with the training of a single type of common natural language processing (NLP) model greatly surpassed the values that are attributed to familiar consumption. Namely, the training of an AI model under such conditions yields approximately 600,000 lb of carbon dioxide emissions, whereas using a car for a lifetime produces one fifth of the same amount. 

Of course, there is also a concern with the amount of energy used by artificial intelligence facilities. In such regard, Alex De Vries (2023) found out in a study that, by 2027, the AI industry could be consuming between 85 to 134 terawatt hours (Twh) annually, which compares to the amount of energy used by a small country such as the Netherlands. Additionally, GenAI tools may use nearly 33 times more energy to carry out a task than task-specific software would (World Economic Forum 2024). What is more, the extraction of natural resources that integrate the components of AI hardware can constitute a source of worry. In an interview, Yale’s Associate Professor Yuan Yao explains that the supply chain of these parts requires partaking in activities such as mining and metal production, that may lead to soil erosion and pollution.  

Interestingly, Wang et al. (2024) suggest that the amount of e-waste (discarded electrical or electronic devices) generated could end up comprising a total of 1.2–5.0 million tons until 2030, depending on the pace of the industry’s growth. According to the World Health Organization, if e-waste is unreliably recycled, it can release up to a thousand different chemical substances, including known neurotoxicants such as lead.  

As one becomes aware of the ethical concerns that come with AI development, and therefore its use, we can start to address these issues: by both reflecting on policies that can be implemented to mitigate the harm of such outbreaking technology and aiming to make more considerate and sustainable use of GenAI.  

Madalena Martinho do Rosário

External VP

Mª Francisca Pereira

President

Sources:

Ferrante, Elena. 2022. In the Margins: On the Pleasures of Reading and Writing. UK: Europa Editions. 

Appel, Gila, Juliana Neelbauer, and David A. Schweidel. 2023. “Generative AI Has an Intellectual Property Problem”. Harvard Business Review. Accessed January 30, 2025. https://hbr.org/2023/04/generative-ai-has-an-intellectual-property-problem  

Brown, Sara. 2021. “Machine learning, explained”. MIT Sloan. Accessed January 31, 2025. https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained  

Wilkinson, Alissa, and Emily Stewart. “The Hollywood writers’ strike is over — and they won big”. VOX. Accessed January 30, 2025. https://www.vox.com/culture/2023/9/24/23888673/wga-strike-end-sag-aftra-contract  

Kanungo, Alokya. 2023. “The Green Dilemma: Can AI Fulfil Its Potential With”. Earth.org. Accessed January 31, 2025. https://earth.org/the-green-dilemma-can-ai-fulfil-its-potential-without-harming-the-environment/  

Strubell, Emma, Ananya Ganesh, and Andrew McCallum. 2020. Energy and Policy Considerations for Deep Learning in NLP. Annual Meeting of the Association for Computational Linguistics. https://doi.org/10.48550/arXiv.1906.02243 

Kemene, Eleni, Bart Valkhof, and Thapelo Tladi. 2024. “AI and energy: Will AI help reduce emissions or increase demand? Here’s what to know”. World Economic Forum. Accessed February 1, 2025. https://www.weforum.org/stories/2024/07/generative-ai-energy-emissions/  

De Vries, Alex. 2023. “The growing energy footprint of artificial intelligence.” Joule 7(10): 2191-2194. https://doi.org/10.1016/j.joule.2023.09.004 

YSE News. 2024. “Can We Mitigate AI’s Environmental Impacts?”. Accessed January 30, 2025. https://environment.yale.edu/news/article/can-we-mitigate-ais-environmental-impacts  

Peng Wang, Ling-Yu Zhang, Asaf Tzachor & Wei-Qiang Chen. 2024. “E-waste challenges of generative artificial intelligence”. Nature Computational Science 4: 818–823 https://doi.org/10.1038/s43588-024-00712-6  

World Health Organization. 2024. “Electronic waste (e-waste)”. WHO. Accessed February 1, 2025. https://www.who.int/news-room/fact-sheets/detail/electronic-waste-(e-waste)  

———. 2025b. “Number of ChatGPT Users (February 2025).” DemandSage. January 31, 2025. https://www.demandsage.com/chatgpt-statistics/. 

———. 2025c. “DeepSeek: Everything You Need to Know About the AI Chatbot App.” TechCrunch, January 31, 2025. https://techcrunch.com/2025/01/28/deepseek-everything-you-need-to-know-about-the-ai-chatbot-app/. 

“How Generative AI Can Boost Highly Skilled Workers’ Productivity | MIT Sloan.” 2023. MIT Sloan. October 19, 2023. https://mitsloan.mit.edu/ideas-made-to-matter/how-generative-ai-can-boost-highly-skilled-workers-productivity. 

UNESCO. n.d. Artificial Intelligence – Recommendation Ethics | UNESCO. UNESCO. https://www.unesco.org/en/artificial-intelligence/recommendation-ethics 

Campbell, Caroline, and Lorna Waddington. 2024. “Academic Integrity Strategies: Student Insights.” Journal of Academic Ethics 22 (1): 33–50. https://doi.org/10.1007/s10805-024-09510-1.Glossary – ENAI. (n.d.). https://www.academicintegrity.eu/wp/glossary/ 

Malmström, H., Stöhr, C., & Ou, A. W. (2023). Chatbots and other AI for learning: A survey of use and views among university students in Sweden. (Chalmers Studies in Communication and Learning in Higher Education 2023:1) https://doi.org/10.17196/cls.csclhe/2023/01 

———. 2024b. “Perceptions and Use of AI Chatbots Among Students in Higher Education: A Scoping Review of Empirical Studies.” Education Sciences 14 (8): 922. https://doi.org/10.3390/educsci14080922. 

Farazouli, Alexandra, Teresa Cerratto-Pargman, Klara Bolander-Laksov, and Cormac McGrath. 2023. “Hello GPT! Goodbye Home Examination? An Exploratory Study of AI Chatbots Impact on University Teachers’ Assessment Practices.” Assessment & Evaluation in Higher Education 49 (3): 363–75. https://doi.org/10.1080/02602938.2023.2241676. 

The New York Times. 2023. The Times Sues Open AI And Microsoft Over AI Use Of Copyrighted Work. December 27, 2023. The New York Times. https://www.nytimes.com/2023/12/27/business/media/new-york-times-open-ai-microsoft-lawsuit.html 

“Total Global AI Investment 2015-2022 | Statista.” 2024. Statista. August 12, 2024. https://www.statista.com/statistics/941137/ai-investment-and-funding-worldwide/. 

“How Much Water Does AI Consume? The Public Deserves to Know – OECD.AI.” n.d. https://oecd.ai/en/wonk/how-much-water-does-ai-consume. 

Li, Yang, Islam, Ren. Making AI Less “Thirsty”: Uncovering and Addressing the Secret Water Footprint of AI Models. (2025). https://arxiv.org/pdf/2304.03271 

Microfinance Interventions and Their Impact on Women´s Empowerment and in Developing Countries 

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What is Microfinance? 

Microfinance is a financial service that provides small loans, savings accounts, insurance, and other financial products to individuals who typically lack access to traditional banking services. It targets low-income individuals, particularly in rural and underserved areas, who may not have collateral or a credit history to qualify for loans from commercial banks. It has gained attention as a tool for inclusive finance and sustainable development, with initiatives implemented worldwide to expand access to financial services for marginalized and vulnerable populations. The service has the potential to empower individuals, particularly women, by giving them the means to create livelihoods, build assets, and improve their standard of living. Thereby, it aims to alleviate poverty by providing financial resources to support income-generating activities, such as starting or expanding small businesses, purchasing livestock or equipment, or investing in education and healthcare.  

How can it be bearer of importance to women? 

Its relevant and important for women’s empowerment, especially in rural areas, due to several reasons, such as financial inclusion, economic empowerment, poverty alleviation, social impact, and risk mitigation.  An undeniable proof of that is the fact that by 2006 microfinance services had reached over 79 million of the poorest women (Daley-Harris 2007 cited in ILO 2008). 

Financial inclusion  

Women, particularly in developing countries, often face barriers to accessing formal financial services such as bank accounts, loans, and savings. Microfinance provides them with access to financial resources that they may not otherwise have, empowering them to participate in economic activities and make financial decisions. 

Economic empowerment 

Microfinance enables women to start or expand small businesses, generate income, and become economically self-sufficient. By providing them with loans, savings accounts, and other financial services, microfinance helps women to invest in income-generating activities, improve their livelihoods and support their families. 

Poverty alleviation  

Women constitute a significant proportion of the world´s poor population. Microfinance programs specifically targeting women can contribute to poverty alleviation by providing them with the means to lift themselves out of poverty. By investing in women’s economic activities, microfinance helps to create opportunities for income generation and asset accumulation, ultimately improving their living standards. 

Women´s Empowerment 

Access to financial resources through microfinance can enhance women’s autonomy and decision-making power within their households and communities. As women become financially independent, they gain greater control over household finances, education, healthcare, and other important aspects of their lives. This empowerment can lead to positive social outcomes, such as improved gender equality and women´s rights. 

Social impact  

Investing in women’s economic empowerment through microfinance can have broader social benefits. Studies have shown that when women have control over household income, they tend to prioritize spending on the well-being of their families. Consequently, microfinance programs targeting women can have ripple effects on community development and poverty reduction. 

Risk Mitigation 

Women often face greater financial vulnerability due to factors such as lower incomes, limited access to formal employment, and social and cultural constraints. Microfinance can help mitigate these risks by providing women with financial tools to cope with emergencies, smooth consumption and build resilience against economic shocks. 

Microfinance in developing countries 

Microcredit programs have been implemented in developing countries such as Bangladesh, India, or Cambodia since 1976 and its relevant to understand if and how it’s a beneficial initiative. To answer this concerns, it was conducted a study focused on the development of microfinance programs in Ethiopia and how it changed the lives of who was targeted. Ethiopia is known for being one of the poorest and underdeveloped countries (68.7% of the population, 82,679 thousand people in 2021, is multidimensionally poor while an additional 18.4% is classified as vulnerable to multidimensional poverty, 22,076 thousand people in 2021). 

For the past two decades, microfinance institutions have held significant sway as a pivotal development initiative in Ethiopia. The genesis of this movement and its subsequent expansion in the country can be traced back to the enactment of legislation postulated after the 1996 proclamation. This legislative milestone stands as a cornerstone in the inception and evolution of microfinance across this country. Notably, there has been a steady escalation in female engagement within the microfinance sphere. All microfinance enterprises share a unified aspiration towards ameliorating poverty and fostering the economic empowerment of women.  

The main aim of the inquiry is to analyse the impact on microfinance programs on women´s economic empowerment. A sample of 346 women that were clients of those initiatives were questioned and examined for a deeper understanding of the debate in question. With the help of tools such as multiple regression and sampled t-test data analysis, was revealed that age, marital status, education level, credit amount, and number of trainings have a significant impact on women’s economic development. 

The results of the paired sample t-test unveiled noteworthy disparities in mean values pre- and post-engagement with microfinance services, particularly concerning income, asset accumulation, and savings. Microfinance interventions evince a discernible positive impact on women’s economic empowerment, manifesting through augmented independent income streams, heightened asset portfolios, and increased monthly savings. Furthermore, the investigation underscored the constructive role of microfinance in nurturing women’s entrepreneurial acumen and fostering their exposure to business opportunities. 

Despite this article being more focused on the effects of microfinance in developing countries, because of how the impact is noticeable, it’s also important to emphasise the fact that also it has also reached and in a growing scale, developed countries, like Spain, that you can read more about in one of the links in the references focused on the Barcelona case. 

Conclusion 

Overall, by addressing the unique financial needs and challenges faced by women, microfinance plays a crucial role in promoting women´s economic empowerment, reducing poverty, and advancing gender equality with the help of its programs that promote an inclusive and sustainable development. Also, it has been proven to be beneficial to countries in development, being a fundamental tool for growth, prosperity, and equality of opportunity. 

References: 

ILO. 2008. “Small change, Big changes: Women and Microfinance”. Geneva, ILO.  wcms_091581.pdf (ilo.org) 

Leight Lebos, Jessica. 2022. “How microfinance supports livelihoods in developing countries”. Kiva. Consulted in 01/05/2024. https://www.kiva.org/blog/how-microfinance-supports-livelihoods-in-developing-countries 

Lorenzo Vidal, Raquel, and Julia Soler Agustí. 2017. “Microcredit in the developed countries: the case of Barcelona”. https://migrant-integration.ec.europa.eu/sites/default/files/2019-10/EWI05-Microcreditinthedevelopedcountries_thecaseofBarcelona.pdf 

Mengstie, Belay. 2022. “Impact of microfinance on women’s economic empowerment”. J Innov Entrep 11 (55). https://doi.org/10.1186/s13731-022-00250-3 

Raid, Dr. Moodhi, Nisar Ahmad, Dr. Hisham Alhawal, and Dr. Jumah Ahmad Alzyadat. 2023. “Impact of Microfinance on Poverty Alleviation in Developing Countries: The Case of Pakistan”. http://dx.doi.org/10.2139/ssrn.4402017 

Laura Casanova