24 papers · ranked by Valyu relevance
Mariel A. Pfeifer, Julio J. Cordero, Julie Dangremond Stanton
STEM instructors are encouraged to adopt active learning in their courses, yet our understanding of how active learning affects different groups of students is still developing. One group often overlooked in higher education research is students with disabilities. Two of the most commonly occurring disabilities on…
Gijs van Tulder, Marco Loog
An interesting but not extensively studied question in active learning is that of sample reusability: to what extent can samples selected for one learner be reused by another? This paper explains why sample reusability is of practical interest, why reusability can be a problem, how reusability could be improved by…
Amol Kulkarni, Janis Terpenny, Vittaldas Prabhu, Tao Peng
Identifying failure modes is an important task to improve the design and reliability of a product and can also serve as a key input in sensor selection for predictive maintenance. Failure mode acquisition typically relies on experts or simulations which require significant computing resources. With the recent advances…
Marcos E García-Ojeda, Michele K Nishiguchi
Teaching students at all levels of education has undergone extensive changes, particularly in the past decade. Our present student population has transformed dramatically in the 21st century due to the changing demographics of the nation, an increasing use of technology both inside and outside the classroom, along with…
Paul Francoeur, Daniel Penaherrera, David Koes
The immense size of chemical space, the relative scarcity of high quality data, and the cost of running experiments to accurately measure molecular properties makes active learning (AL) an attractive approach to efficiently explore the space and train high-quality models for molecular property prediction. While AL is…
Xinjian Cen, Rachel J. Lee, Christopher Contreras, Melinda T. Owens + 1 more
Active learning, including student thinking and discussion in class, has been shown to increase student learning gains. However, it is less clear how variations in how instructors implement active learning affect student gains. Our study aims to investigate the extent to which the time spent on individual episodes of…
Judit Sánchez, Marta Lesmes, Clara Azpeleta, Beatriz Gal
Background Engaging, student-centered active learning activities, such as team-based learning (TBL) and laboratory practices, is beneficial to integrate knowledge, particularly in Medicine degree. Previously, we designed and implemented workstation learning activities (WSLA) inspired by TBL, which proved effective for…
Mallory A. Jackson, Hongjiao Liu, Sungmin Moon, Jennifer H. Doherty + 1 more
Myriad studies support the claim that active learning improves student academic performance in STEM, yet lecture remains the dominant form of instruction. Faculty offer multiple reasons for not using active learning with many expressing confusion as to what active learning is. Contributing to that confusion is the fact…
Elizaveta Surzhikova, Jonny Proppe
Increasingly more research areas rely on machine learning methods to accelerate discovery while saving resources. Machine learning models, however, usually require large datasets of experimental or computational results, which in certain fields— such as (bio)chemistry, materials science, or medicine— are rarely given…
Derek van Tilborg, Francesca Grisoni
Deep learning is accelerating drug discovery. However, current approaches are often affected by limitations in the available data, e.g., in terms of size or molecular diversity. Active deep learning has an untapped potential for low-data drug discovery, as it allows to improve a model iteratively during the screening…
D. J. Lees-Murdock, D. Khan, R. Irwin, J. Graham + 3 more
'B. O’Hagan' 'S. McClean'] Introduction: Active learning is a useful tool to enhance student engagement and support learning in diverse educational situations. We aimed to assess the efficacy of an active learning approach within a large interprofessional first year Medical Cell Biology module taken by six healthcare…
Shangmou Xu, Vicente Velasco, Mariah J. Hill, Elisa Tran + 31 more
We updated a recent meta-analysis of active learning’s impact on student achievement in undergraduate STEM courses by following the same protocol to evaluate studies published from 2010-2017. We screened 1659 papers, coded 1294, and found 210 that met five pre-established inclusion criteria and six pre-established…
Alexander Muacevic, John R Adler, Kalyan Kandra, Praneetha Vennam
Graduate medical education (GME) is undergoing a significant pedagogical transformation, moving away from traditional, passive learning environments toward more dynamic, learner-centered approaches. This narrative review examines the implementation and impact of active teaching methods in GME, with a specific focus on…
Yannick Ureel, Maarten R. Dobbelaere, Yi Ouyang, Kevin De Ras + 3 more
By combining machine learning with design of experiments, so-called active machine learning, more efficient and cheaper research can be conducted. Machine learning algorithms are more flexible, and are better at investigating the processes spanning all length scales of chemical engineering. While the active machine…
Arshia Soltani Moakhar, Tanapoom Laoaron, Faraz Ghahremani, Kiarash Banihashem + 1 more
This paper advances the theoretical understanding of active learning label complexity for decision trees as binary classifiers. We make two main contributions. First, we provide the first analysis of the disagreement coefficient for decision trees—a key parameter governing active learning label complexity. Our analysis…
Raquel Lopes, Ana Baptista, Sergii Tukaiev, Vaitsa Giannouli + 1 more
The integration of digital tools in teaching remains a challenge for many educators, often due to resistance to change and limited training. Drawing on Self-Determination Theory, as proposed by Deci and Ryan, and Cognitive Load Theory, developed by Sweller, this exploratory study examines student motivation and…
Arnaldo Perez, Jacqueline Green, Mohammad Moharrami, Silvia Gianoni-Capenakas + 5 more
Seventy-six student reaction evaluations alone or combined were conducted. In these evaluations, active learning was perceived to improve satisfaction in 66 studies (86.8%) and knowledge acquisition in 4 studies (5.3%). Sixty-five of these evaluations or studies compared active learning and lectures, 3 compared two…
Laura Desirèe Di Paolo, Ben White, Avel Guénin-Carlut, Axel Constant + 1 more
'Andy Clark'] Human learning essentially involves embodied interactions with the material world. But our worlds now include increasing numbers of powerful and (apparently) disembodied generative artificial intelligence (AI). In what follows we ask how best to understand these new (somewhat ‘alien’, because of their…
Davide Cacciarelli, Murat Külahçı
Online active learning is a paradigm in machine learning that aims to select the most informative data points to label from a data stream. The problem of minimizing the cost associated with collecting labeled observations has gained a lot of attention in recent years, particularly in real-world applications where data…
Sid Ijju
Active learning algorithms have been an integral part of recent advances in artificial intelligence. However, the research in the field is widely varying and lacks an overall organizing leans. We outline a Markovian formalism for the field of active learning and survey the literature to demonstrate the organizing…
Melanie M Cooper, Marcos D. Caballero, Justin H. Carmel, Erin M. Duffy + 11 more
In recent years, much of the emphasis for transformation of introductory STEM courses has focused on “active learning”, and while this approach has been shown to produce more equitable outcomes for students, the construct of “active learning” is somewhat ill-defined, and can encompass a wide range of pedagogical…
Francesco Balzan, Pedro P. Santos, Maurizio Gabbrielli, Mahault Albarracin + 1 more
'Mahault Albarracin' 'Manuel Lopes'] Human education transcends mere knowledge transfer, it relies on co-adaptation dynamics the mutual adjustment of teaching and learning strategies between agents. Despite its centrality, computational models of co-adaptive teacher-student interactions (T-SI) remain underdeveloped. We…
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Developing generalizable machine learning models with minimal data remains a central challenge in materials informatics. Effective models can significantly reduce costly computational simulations and time-intensive experimentation by providing reliable predictions of material properties. In this work, we investigate…
Yuriy Khalak, Gary Tresadern, David F. Hahn, Bert L. de Groot + 1 more
Drug discovery can be thought as a search for a needle in a haystack. Finding the initial active hit molecules, the optimal decoration of lead molecule analogues, to final clinical candidate selection is an on-going trade-off between applying the best methods versus the cost of assessing the large available chemical…