About
45
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Introduction
Dr. Mirka Saarela currently works at the Department of Mathematical Information Technology, University of Jyväskylä. Mirka does research in Algorithms, Artificial Neural Network and Artificial Intelligence. Their current project is 'LSEA algorithms'.
Publications
Publications (45)
The Finnish publication channel quality ranking system was established in 2010. The system is expert-based, where separate panels decide and update the rankings of a set of publications channels allocated to them. The aggregated rankings have a notable role in the allocation of public resources into universities. The purpose of this article is to a...
Principal component analysis is one of the most popular machine learning and data mining techniques. Having its origins in statistics, principal component analysis is used in numerous applications. However, there seems to be not much systematic testing and assessment of principal component analysis for cases with erroneous and incomplete data. The...
Curricula for Computer Science (CS) degrees are characterized by the strong occupational orientation of the discipline. In the BSc degree structure, with clearly separate CS core studies, the learning skills for
these and other required courses may vary a lot, which is shown in students’ overall performance. To analyze this situation, we apply nons...
The Programme for International Student Assessment (PISA) is a worldwide study that assesses the proficiencies of 15-year-old students in reading, mathematics, and science every three years. Despite the high quality and open availability of the PISA data sets, which call for big data learning analytics, academic research using this rich and careful...
A clustering result needs to be interpreted and evaluated for knowledge discovery. When clustered data represents a sample from a population with known sample-to-population alignment weights, both the clustering and the evaluation techniques need to take this into account. The purpose of this article is to advance the automatic knowledge discovery...
As technology changes how teachers traditionally teach, they are becoming interested in the possible benefits of Artificial Intelligence (AI) in education, like personalized learning and more efficient administrative tasks. However, using AI tools in education also comes with challenges such as teachers needing to be familiar with technology, resis...
Gamification has been a significant topic in the field of education for a decade, and in the educational context, gamification tends to look at learners' motivation, motivational learning behavior, or engagement in activities. To motivate students in the classroom and keep them engaged in activities, students' motivation is a crucial factor that mu...
This systematic literature review employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of explainable AI (XAI) over the past three years. From an initial pool of 664 articles identified through the Web of Science database, 512 peer-reviewed journal articles met the in...
The ethical use of engagement data in online education is a growing concern as institutions increasingly rely on learning analytics. This study explores students' perceptions of engagement data collection and usage by focusing on their attitudes towards privacy and data management. We conducted a survey among students (n=108) who participated in on...
Cognition and learning are exceedingly modeled as an associative activity of connectionist neural networks. However, only a few such models exist for continuous reading, which involves the delicate coordination of word recognition and eye movements. Moreover, these models are limited to only orthographic level of word processing with predetermined...
Data analytics is widely accepted as a crucial aspect of effective school leadership, yet its utilization by principals has not been thoroughly examined in scholarly works. The potential of Educational Data Mining Tools (EDM) to provide a "big picture" for principals to address equity gaps among students is overlooked in the literature. This articl...
Countries adopt different strategies and policies to ensure the implementation of ethical data processing and within this framework, they may encounter challenges. In this paper , we analyze the main issues regarding ethical data gover-nance of students with special needs in post-Soviet countries and compare them. The reason why we selected post-So...
This paper presents an umbrella review synthesizing the findings of explainability studies within the Educational Data Mining (EDM) and Learning Analytics (LA) domains. By systematically reviewing existing reviews and adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we identified 49 secondary s...
Explainable artificial intelligence (XAI) refers to machine learning techniques, or general methods in artificial intelligence, for which the underlying decision logic and outcomes can be explained. It addresses the tradeoff between powerful but opaque machine learning models by shedding light into the black boxes. Thus, XAI are applicable only for...
This chapter deals with the learning analytics technique called student agency analytics and explores its foundational technologies and their potential implications for adaptive teaching and learning. Student agency is vital to consider as it can empower students to take control of their learning, fostering autonomy, meaningful experiences, and imp...
Even though Azerbaijan is considered a highly educated country from the perspective of schooling years and completed education level, student learning outcomes are under-performing, according to the World Bank. Due to limited resources such as classroom size, access to world-class educational materials, and high-qualified teachers, particularly stu...
Background
Measurement of students' self‐regulation skills is an active topic in education research, as effective assessment helps devising support interventions to foster academic achievement. Measures based on event tracing usually require large amounts of data (e.g., MOOCs and large courses), while aptitude measures are often qualitative and nee...
Digital technologies in teaching and learning in higher education have the potential to enhance student agency. Student agency is an essential resource to nurture, especially at times when students face challenges emerging from the volatile, uncertain, complex, and ambiguous world. In addition, contemporary policymaking has identified the importanc...
Skin cancer is one of the most prevalent of all cancers. Because of its being widespread and externally observable, there is a potential that machine learning models integrated into artificial intelligence systems will allow self-screening and automatic analysis in the future. Especially, the recent success of various deep machine learning models s...
The pervasiveness of technical systems in our lives calls for a broad understanding of the interaction between humans and technology. Affinity for technology interaction (ATI) scale measures the tendency of a person to actively engage or to avoid interaction with technological systems, including both software and physical devices. This research pre...
Several studies have shown that complex nonlinear learning analytics (LA) techniques outperform the traditional ones. However, the actual integration of these techniques in automatic LA systems remains rare because they are generally presumed to be opaque. At the same time, the current reviews on LA in higher education point out that LA should be m...
Explainable artificial intelligence is an emerging research direction helping the user or developer of machine learning models understand why models behave the way they do. The most popular explanation technique is feature importance. However, there are several different approaches how feature importances are being measured, most notably global and...
This Research Full Paper presents an examination of the relationships between course satisfaction and student agency resources in engineering education. Satisfaction experienced in learning is known to benefit the students in many ways. However, the varying significance of the different factors of course satisfaction is not entirely clear. We used...
We propose a general framework for realistic data generation and simulation of complex systems in the health domain. The main use cases of the framework are predicting the development of risk factors and disease occurrence, evaluating the impact of interventions and policy decisions, and statistical method development. We present the fundamentals o...
Making in education is an emergent practice focusing on learners as creators of things in a collaborative fashion while promoting knowledge construction through technology, design, and creative self-expression. Teachers’ (n=33) opinions about making were studied using an online questionnaire after they had attended an online course for professional...
In this paper, we use student agency analytics to examine how university students who assessed to have low agency resources describe their study experiences. Students (n=292) completed the Agency of University Students (AUS) questionnaire. Furthermore, they reported what kinds of restrictions they experienced during the university course they atten...
The publication indicator of the Finnish research funding system is based on a manual ranking of scholarly publication channels. These ranks, which represent the evaluated quality of the channels, are continuously kept up to date and thoroughly reevaluated every four years by groups of nominated scholars belonging to different disciplinary panels....
The paper proposes to analyze a data set of Finnish ranks of academic publication channels with Extreme Learning Machine (ELM). The purpose is to introduce and test recently proposed ELM-based mislabel detection approach with a rich set of features characterizing a publication channel. We will compare the architecture, accuracy, and, especially, th...
Technology integration promises better quality in education. This integration is challenging to accomplish, especially for teachers in a developing country like Nigeria where the demand for education remains a struggle in the face of dwindling resources. The technological pedagogical content knowledge (TPACK) framework promotes designing strategies...
On-the-job medical training is known to be challenging due to the fast-paced environment and strong vocational profile. It relies on on-site supervisors, mainly doctors and nurses with long practical experience, who coach and teach their less experienced colleagues, such as residents and healthcare students. These supervisors receive pedagogical tr...
The paper proposes to analyze a data set of Finnish ranks of academic publication channels with Extreme Learning Machine (ELM). The purpose is to introduce and test recently proposed ELM-based mislabel detection approach with a rich set of features characterizing a publication channel. We will compare the architecture, accuracy, and, especially, th...
Hospitalization of elderly patients can lead to serious adverse effects on their functional capability. Identifying the underlying factors leading to such adverse effects is an active area of medical research. The purpose of the current paper is to show the potential of artificial intelligence in the form of machine learning to complement the exist...
Although Germany's largest distance university collects huge amounts of student data from various sources there are hardly any efforts leveraging these data for improvement of learning (environments) and organization of studies. This paper presents firsts thoughts of how learning analytics could be utilized to produce and analyze useful models base...
Johdanto PISA (Programme for International Students Assessment) on joka kolmas vuosi toteutettava kansainvälinen koulutusjärjestelmävertailu, joka tuottaa julkisesti saatavilla olevaa laajaa aineistoa koulutuksen tilasta ja tuloksista sekä koulun ulkopuolella tapahtuvasta oppimisesta. PISA 2015-tutkimuksessa oppilaiden osaamista oli ensimmäisen ker...
Academic advising is a process between the advisee, adviser and the academic institution which provides the degree requirements and courses contained in it. Content-wise planning and management of the student’ study path, guidance on studies and academic career support is the main joint activity of advising. The purpose of this article is to propos...
Large-scale educational assessment studies (LSAs) regularly collect massive amounts of very rich cognitive and contextual data of whole student populations. Currently, LSAs are limited to reporting student proficiencies in the form of plausible values (PVs). PVs are random draws from the posterior distribution of a student's ability, which is based...
Certain stereotypes can be associated with people from different countries. For example, the Italians are expected to be emotional, the Germans functional, and the Chinese hard-working. In this study, we cluster all 15-year-old students representing the 68 different nations and territories that participated in the latest Programme for International...
Clustering as an unsupervised technique is predominantly used in unweighted settings. In this paper, we present an efficient version of a robust clustering algorithm for sparse educational data that takes the weights, aligning a sample with the corresponding population, into account. The algorithm is utilized to divide the Finnish student populatio...
The Programme for International Student Assessment, PISA, is a worldwide study to assess knowledge and skills of 15-year-old students. Results of the latest PISA survey conducted in 2012 were published in December 2013. According to the results, Finland is one of the few countries where girls performed better in mathematics than boys. The purpose o...