Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…

Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…

Text analytics in education has evolved to form a critical component of the future SMART campus architecture. Sentiment analysis and qualitative feedback from students is now a crucial application domain of text analytics relevant to institutions. The implementation of sentiment analysis helps understand learners' appreciation of lessons, which…

Mathematics education is like many scientific disciplines witnessing an increase in scientific output. Examining and reviewing every paper in an area in detail are time-consuming, making comprehensive reviews a challenging task. Unsupervised machine learning algorithms like topic models have become increasingly popular in recent years. Their…

The outbreak of COVID-19 has caused significant disruption in all sectors and industries around the world. To tackle the spread of the novel coronavirus, the learning process and the modes of delivery had to be altered. Most courses are delivered traditionally with face-to-face or a blended approach through online learning platforms. In addition,…

Recommender systems have become one of the main tools for personalized content filtering in the educational domain. Those who support teaching and learning activities, particularly, have gained increasing attention in the past years. This growing interest has motivated the emergence of new approaches and models in the field, in spite of it, there…

Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns…

Despite considerable advances in knowledge tracing algorithms, educational technologies that use this technology typically continue to use older algorithms, such as Bayesian Knowledge Tracing. One key reason for this is that contemporary knowledge tracing algorithms primarily infer next-problem correctness in the learning system, but do not…

The focus of ethics in learning analytics (LA) frameworks and guidelines is predominantly on procedural elements of data management and accountability. Another, less represented focus is on the duty to act and LA as a moral practice. Data feminism as a critical theoretical approach to data science practices may offer LA research and practitioners…

With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…

Explicable AI in education (XAIED) has been proposed as a way to improve trust and ethical practice in algorithmic education. Based on a critical review of the literature, this paper argues that XAI should be understood as part of a wider socio-technical turn in AI. The socio-technical perspective indicates that explicability is a relative term.…

To improve the calibration accuracy and calibration efficiency of cognitive diagnostic computerized adaptive testing (CD-CAT) for new items and, ultimately, contribute to the widespread application of CD-CAT in practice, the current article proposed a Gini-based online calibration method that can simultaneously calibrate the Q-matrix and item…

This article considers the challenges of using artificial intelligence (AI) and machine learning (ML) to assist high-stakes standardised assessment. It focuses on the detrimental effect that even state-of-the-art AI and ML systems could have on the validity of national exams of secondary education, and how lower validity would negatively affect…

The influence of algorithms on society is increasing due to their growing presence in all areas of daily life. Although we are not always aware of it, they sometimes usurp the identity of other social actors. The main purpose of this article is to address the meta-research on the field of artificial intelligence and communication from a holistic…

Learning analytics offer centralization of a particular understanding of learning, teaching, and student support alongside data-informed insight and foresight. As such, student-related data in higher education can be imagined and enacted as a 'data frontier' in which the data gaze is expanding, intensifying, and performing new meanings and…