Entity resolution is a fundamental task in data integration. Recent studies of this problem, including active learning, crowdsourcing, and pay-as-you-go approaches, have started to involve human users in the loop to carry out interactive entity resolution tasks, namely to invite human users to judge whether two entity descriptions refer to the same real-world entity. This process of judgment re...

As the perception of beauty is subjective across individuals, evaluating the objective aesthetic value of an image is a challenging task in image retrieval system. Unlike current online photo sharing services that take the average rating as the aesthetic score, our system integrates various ratings from different users by jointly modeling images and users’ expertise in a regression framework. I...

In this paper, we present an interactive approach for the classification of sound objects in electro-acoustic music. For this purpose, we use relevance feedback combined with active-learning segment selection in an interactive loop. Validation and correction information given by the user is injected in the learning process at each iteration to achieve more accurate classification. Three active ...

For learning problems where human supervision is expensive, active query selection methods are often exploited to maximise the return of each supervision. Two problems where this has been successfully applied are active discovery – where the aim is to discover at least one instance of each rare class with few supervisions; and active learning – where the aim is to maximise a classifier’s perfor...

Over the past few years the question of whether the lecture is an effective teaching method has been one of the most heatedly debated topics in the field of higher education. While research on the effectiveness of lectures has been carried out since at least the 1960s, the value of the lecture has been increasingly questioned recently for a number of reasons that include waning lecture attendan...

This study examines the evidence for the effectiveness of active learning. It defines the common forms of active learning most relevant for engineering faculty and critically examines the core element of each method. It is found that there is broad but uneven support for the core elements of active, collaborative, cooperative and problem-based learning.

Background: Research has shown that active learning promotes student learning and increases retention rates of STEM undergraduates. Yet, instructors are reluctant to change their teaching approaches for several reasons, including a fear of student resistance to active learning. This paper addresses this issue by building on our prior work which demonstrates that certain instructor strategies ca...

Recent evidence for the effectiveness of active learning interventions has led educators to advocate for widespread adoption of active learning in undergraduate science, technology, engineering, and mathematics courses. Active learning interventions implement technology and collaboration to engage students actively with the content. Yet, it is unclear how these features contribute to their effe...

When using active learning, smaller batch sizes are typically more efficient from a learning efficiency perspective. However, in practice due to speed and human annotator considerations, the use of larger batch sizes is necessary. While past work has shown that larger batch sizes decrease learning efficiency from a learning curve perspective, it remains an open question how batch size impacts m...

An active learning approach was developed and implemented to address inherent difficulties in teaching subjects in engineering dynamics. A variety of active learning exercises have been introduced to replace a portion of traditional lecture presentations. Demonstrations sessions involving student participation in simulations using MECHANICA_Motion, physical models and Videos have been introduce...