Maria Cutumisu
Biographic Data
| ID | 5707259 |
|---|---|
| NAME | Maria Cutumisu |
| GIVEN NAMES | Maria |
| FAMILY NAME | Cutumisu |
| SIGNATURE | CUTUMISU M |
| AFFILIATIONS | University of Alberta |
| ORCID | 0000-0003-2475-9647 |
| VERIFIED | Yes |
| TOTAL WORKS | 21 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 21 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Profiling Pre-service Teachers’ Computational Thinking
Computational thinking (CT) is a vital skill set for pre-service teachers who will need to foster computational literacy in K–12 classrooms, yet the factors influencing their CT skills remain less understood than those for K–12 students or in-service teachers. This study leverages multimodal data to investigate how pre-service teachers (n=128) differ in CT skills, the predictive role of metacognitive strategies and prior coding experience, and va…
A systematic review of human-LLM interactions in computational thinking empirical studies
Using machine learning algorithms to predict students' general self-efficacy in Pisa 2018
Self-efficacy is a critical psychological construct that exerts a positive impact on students' learning experiences and global well-being. Previous studies explored the factors related to the development and variation of students' self-efficacy, but they only focused on a limited set of predictors. To gain a more comprehensive understanding of the factors affecting self-efficacy, it is necessary to build a predictive model based on a large number…
Assessing Numerical Analysis Performance with the Practi Mobile App
Numerical analysis is a unique combination of mathematical and computing skills. It facilitates a deeper understanding of data analytics and machine learning software libraries, which are exploding in use and importance. However, it is a topic that continues to challenge students because it requires a confluence of conceptual, procedural, and computational skills and associated pedagogies. Therefore, it is valuable to identify effective pedagogie…
Predicting the Mathematics Literacy of Resilient Students from High‐performing Economies
Mathematics is a crucial yet challenging subject for all students. Therefore, it is important to understand the role of academic resilience in mathematics, which enables students to overcome academic challenges. This study applied two machine learning algorithms, Lasso Regression (LR) and Random Forest (RF), to predict the mathematics literacy of resilient students from high-performing economies across cultures in PISA 2022. The findings indicate…
A Randomized Controlled Simulation Trial of a Neonatal Resuscitation Digital Game Simulator for Labour and Delivery Room Staff
Labour and delivery room healthcare providers in both groups (RETAIN simulator or video lecture) significantly improved their neonatal resuscitation performance immediately following the intervention, with no group differences. The findings suggest that participants enjoyed interacting with the RETAIN digital game simulator, which provided a similar boost in performance right after use to the more traditional intervention
The Effects of a Digital Game Simulator versus a Traditional Intervention on Paramedics’ Neonatal Resuscitation Performance
Neonatal resuscitation is a skill set that comprises procedures, assessment, decision-making, communication, and teamwork. It is used in an emergency situation in the delivery room with the aim of supporting newborn infants who are not able to begin breathing on their own. Thus, healthcare providers need to refresh their neonatal resuscitation skills periodically, according to the Neonatal Resuscitation Program, to ensure that they can react quic…
Using machine learning to predict student science achievement based on science curriculum type in TIMSS 2019
Most educational systems use either an integrated or a separated science curriculum. However, it is unclear which of these science curricula benefits students more author and existing research provides insufficient information about the implementation details of the curriculum employed. Therefore, this study compares the effects of two science curricula on students' science literacy, drawing on socio-ecological theory and employing educational da…
Predicting teachers’ research reading
Using machine learning to predict UK and Japanese secondary students' life satisfaction in Pisa 2018
BACKGROUND: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. OBJECTIVE: Using ML algorithms, the current study predicts secondary students' life satisfaction from individual-level variables. METHOD: Two supervised ML mode…
The roles of generic and domain-specific mindsets in learning graphic design principles
It is possible that individuals do not endorse a general mindset or theory of intelligence and that their mindset is specific to particular domains. There is currently a dearth of evidence to support this possibility. It is also not known how these two types of mindset influence learning behaviors and outcomes. This study investigates the roles of generic mindsets (i.e. beliefs about general ability) and domain-specific mindsets (i.e. beliefs abo…
Using Structural Equation Modeling to Examine the Relationship Between Preservice Teachers’ Computational Thinking Attitudes and Skills
The growing interest of educational researchers in computational thinking (CT) has led to an expanding literature on assessments of CT skills and attitudes. However, few studies have examined whether CT attitudes influence CT skills. The present study examines the relationship between CT attitudes and CT skills for preservice teachers (PSTs). The Callysto CT test (CCTt) for Teachers was administered to $n\,\,=$ 105 PSTs to measure their CT attitu…
Discovering Clusters of Support Utilization in the Canadian Community Health Survey–Mental Health
Key Information Processes for Thinking Critically in Data-Rich Environments
The objective of the present paper is to propose a refined conception of critical thinking in data-rich environments. The rationale for refining critical thinking stems from the need to identify specific information processes that direct the suspension of prior beliefs and activate broader interpretations of data. Established definitions of critical thinking, many of them originating in philosophy, do not include such processes. A refinement of c…
Feedback choices and their relations to learning are age-invariant starting in middle school
Testing measurement invariance of Pisa 2015 mathematics, science, and ICT scales using the alignment method
University students’ negative emotions in a computer-based examination
Although the effectiveness and experiences of computer-based examinations is a widely investigated area of research, the question of whether and how computer-based assessment limits or heightens the experience of negative test emotions remains largely unexamined. Drawing from the control-value theory of achievement emotions, we investigated undergraduate students’ emotions during an authentic, course-based assessment in a computer-based testing e…
The moderating effect of mindset on the relationship between university students’ critical feedback-seeking and learning
The relation between academic achievement and the spontaneous use of design-thinking strategies
A scoping review of the relationship between students’ ICT and performance in mathematics and science in the Pisa data
Using Topic Modeling to Extract Pre-Service Teachers’ Understandings of Computational Thinking From Their Coding Reflections
Contribution: This paper employs the automatic scoring of short essays as a novel way to determine pre-service teachers' knowledge of and attitudes toward computational thinking (CT) from their written reflections. Implications about designing CT courses for pre-service teachers are discussed. Background: CT is an essential 21st-century competency that supports the development of problem-solving skills. Inspired by computing science problem-solvi…
No prominent works on this page.
Using Topic Modeling to Extract Pre-Service Teachers’ Understandings of Computational Thinking From Their Coding Reflections
Contribution: This paper employs the automatic scoring of short essays as a novel way to determine pre-service teachers' knowledge of and attitudes toward computational thinking (CT) from their written reflections. Implications about designing CT courses for pre-service teachers are discussed. Background: CT is an essential 21st-century competency that supports the development of problem-solving skills. Inspired by computing science problem-solvi…
The moderating effect of mindset on the relationship between university students’ critical feedback-seeking and learning
The relation between academic achievement and the spontaneous use of design-thinking strategies
A scoping review of the relationship between students’ ICT and performance in mathematics and science in the Pisa data
Key Information Processes for Thinking Critically in Data-Rich Environments
The objective of the present paper is to propose a refined conception of critical thinking in data-rich environments. The rationale for refining critical thinking stems from the need to identify specific information processes that direct the suspension of prior beliefs and activate broader interpretations of data. Established definitions of critical thinking, many of them originating in philosophy, do not include such processes. A refinement of c…
Feedback choices and their relations to learning are age-invariant starting in middle school
Testing measurement invariance of Pisa 2015 mathematics, science, and ICT scales using the alignment method
University students’ negative emotions in a computer-based examination
Although the effectiveness and experiences of computer-based examinations is a widely investigated area of research, the question of whether and how computer-based assessment limits or heightens the experience of negative test emotions remains largely unexamined. Drawing from the control-value theory of achievement emotions, we investigated undergraduate students’ emotions during an authentic, course-based assessment in a computer-based testing e…
Using Structural Equation Modeling to Examine the Relationship Between Preservice Teachers’ Computational Thinking Attitudes and Skills
The growing interest of educational researchers in computational thinking (CT) has led to an expanding literature on assessments of CT skills and attitudes. However, few studies have examined whether CT attitudes influence CT skills. The present study examines the relationship between CT attitudes and CT skills for preservice teachers (PSTs). The Callysto CT test (CCTt) for Teachers was administered to $n\,\,=$ 105 PSTs to measure their CT attitu…
Discovering Clusters of Support Utilization in the Canadian Community Health Survey–Mental Health
The roles of generic and domain-specific mindsets in learning graphic design principles
It is possible that individuals do not endorse a general mindset or theory of intelligence and that their mindset is specific to particular domains. There is currently a dearth of evidence to support this possibility. It is also not known how these two types of mindset influence learning behaviors and outcomes. This study investigates the roles of generic mindsets (i.e. beliefs about general ability) and domain-specific mindsets (i.e. beliefs abo…
Assessing Numerical Analysis Performance with the Practi Mobile App
Numerical analysis is a unique combination of mathematical and computing skills. It facilitates a deeper understanding of data analytics and machine learning software libraries, which are exploding in use and importance. However, it is a topic that continues to challenge students because it requires a confluence of conceptual, procedural, and computational skills and associated pedagogies. Therefore, it is valuable to identify effective pedagogie…
Predicting the Mathematics Literacy of Resilient Students from High‐performing Economies
Mathematics is a crucial yet challenging subject for all students. Therefore, it is important to understand the role of academic resilience in mathematics, which enables students to overcome academic challenges. This study applied two machine learning algorithms, Lasso Regression (LR) and Random Forest (RF), to predict the mathematics literacy of resilient students from high-performing economies across cultures in PISA 2022. The findings indicate…
A Randomized Controlled Simulation Trial of a Neonatal Resuscitation Digital Game Simulator for Labour and Delivery Room Staff
Labour and delivery room healthcare providers in both groups (RETAIN simulator or video lecture) significantly improved their neonatal resuscitation performance immediately following the intervention, with no group differences. The findings suggest that participants enjoyed interacting with the RETAIN digital game simulator, which provided a similar boost in performance right after use to the more traditional intervention
The Effects of a Digital Game Simulator versus a Traditional Intervention on Paramedics’ Neonatal Resuscitation Performance
Neonatal resuscitation is a skill set that comprises procedures, assessment, decision-making, communication, and teamwork. It is used in an emergency situation in the delivery room with the aim of supporting newborn infants who are not able to begin breathing on their own. Thus, healthcare providers need to refresh their neonatal resuscitation skills periodically, according to the Neonatal Resuscitation Program, to ensure that they can react quic…
Using machine learning to predict student science achievement based on science curriculum type in TIMSS 2019
Most educational systems use either an integrated or a separated science curriculum. However, it is unclear which of these science curricula benefits students more author and existing research provides insufficient information about the implementation details of the curriculum employed. Therefore, this study compares the effects of two science curricula on students' science literacy, drawing on socio-ecological theory and employing educational da…
Predicting teachers’ research reading
Using machine learning to predict UK and Japanese secondary students' life satisfaction in Pisa 2018
BACKGROUND: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. OBJECTIVE: Using ML algorithms, the current study predicts secondary students' life satisfaction from individual-level variables. METHOD: Two supervised ML mode…
Using machine learning algorithms to predict students' general self-efficacy in Pisa 2018
Self-efficacy is a critical psychological construct that exerts a positive impact on students' learning experiences and global well-being. Previous studies explored the factors related to the development and variation of students' self-efficacy, but they only focused on a limited set of predictors. To gain a more comprehensive understanding of the factors affecting self-efficacy, it is necessary to build a predictive model based on a large number…
Profiling Pre-service Teachers’ Computational Thinking
Computational thinking (CT) is a vital skill set for pre-service teachers who will need to foster computational literacy in K–12 classrooms, yet the factors influencing their CT skills remain less understood than those for K–12 students or in-service teachers. This study leverages multimodal data to investigate how pre-service teachers (n=128) differ in CT skills, the predictive role of metacognitive strategies and prior coding experience, and va…
A systematic review of human-LLM interactions in computational thinking empirical studies
Psychology (16 works) · Computer Science (15 works) · Mathematics education (13 works) · Online Learning and Analytics (9 works) · Innovative Teaching and Learning Methods (5 works) · Social Psychology (5 works) · Pedagogy (4 works) · Academic achievement (3 works) · Artificial Intelligence (3 works) · Computational Thinking (3 works)