By using modern data analysis techniques, this study aims to construct an innovative university English teaching effectiveness evaluation model based on particle swarm algorithm and support vector machine. The model is designed to improve assessment accuracy and personalization. The research process includes the methodology of data collection,…

There is a growing need to empirically evaluate the quality of online instructional interventions at scale. In response, some online learning platforms have begun to implement rapid A/B testing of instructional interventions. In these scenarios, students participate in series of randomized experiments that evaluate problem-level interventions in…

The integration of Internet technology and the collaborative development of smart classrooms is an essential step for colleges and universities to advance English instruction reform. This study utilized data mining (DM) technology to analyze the learning process in college English smart classrooms. The results indicate that the DM algorithm used…

Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

Students with and without disabilities may be educated across various service delivery models (SDMs): general education, cotaught, pull-out, and self-contained. Still, evidence for their relative effectiveness at scale remains limited. Using longitudinal administrative data from Indiana, we measured the effect of different SDMs on test scores,…

Purpose: Although E-learning has been in use for over two decades, running parallel to traditional learning systems, it has gained increased attention due to its vital role in universities in the wake of the COVID-19 pandemic. The primary challenge within E-learning pertains to the maintenance of sustainable effectiveness and the assurance of…

The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…

In the age of big data and analytics, it is important that students learn about artificial intelligence (AI) and machine learning (ML). Machine learning is a discipline that focuses on building a computer system that can improve itself using experience. ML models can be used to detect patterns from data and recommend strategic marketing actions.…

Data modeling is an essential part of IT studies. Learning how to design and structure a database is important when storing data in a relational database and is common practice in the IT industry. Most students need much practice and tutoring to master the skill of data modeling and database design. When a student is in a learning process,…

At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…

Automated content generation for educational games has become an emerging research problem, as manual authoring is often time consuming and costly. In this article, we present a procedural content generation framework that intends to produce educational game content from the viewpoint of both designer and user. This framework generates content by…

Within many preservice teacher education programs in Australia, mentoring is used as the overarching methodology for the professional placement. The professional placement is considered to be a key component of learning to teach, and typically a dyad mentoring model is utilized. However, it is reported that many preservice teachers experience a…

Although game-based learning has been increasingly promoted in education, there is a need to adapt game content to individual needs for personalized learning. Procedural content generation (PCG) offers a solution for difficulty in developing game contents automatically by algorithmic means as it can generate individually customizable game contents…

Automatic assessment of dialogic properties of classroom discourse would benefit several widespread classroom observation protocols. However, in classrooms with low incidences of dialogic discourse, assessment can be highly biased against detecting dialogic properties. In this paper, we present an approach to addressing this imbalanced class…