Professional profiles are unstructured documents where the knowledge and experience of the editor predominate, presenting inconsistencies and ambiguities in terms of the competencies they contain, making complicated the recognition of knowledge and skills necessary for the proposal of university study programs. Also, the identification of…

Propensity score matching and weighting methods are applied to balance covariates and reduce selection bias in the analysis of observational study data, and ultimately estimate a treatment effect. We wish to evaluate the impact of a Supplemental Instruction (SI) program on student success in an Introductory Statistics course. In such student…

As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…

An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…

We introduce a short answer scoring engine made up of an ensemble of deep neural networks and a Latent Semantic Analysis-based model to score short constructed responses for a large suite of questions from a national assessment program. We evaluate the performance of the engine and show that the engine achieves above-human-level performance on a…

In this paper we use historic score-reporting records and test-taker metadata to inform data-driven recommendations that support international students in their choice of undergraduate institutions for study in the United States. We investigate the use of Structural Topic Modeling (STM) as a context-aware, probabilistic recommendation method that…

In this paper, I argue that the fields of artificial intelligence (AI) and education have been deeply intertwined since the early days of AI. Specifically, I show that many of the early pioneers of AI were cognitive scientists who also made pioneering and impactful contributions to the field of education. These researchers saw AI as a tool for…

In interactive e-learning environments such as Intelligent Tutoring Systems, pedagogical decisions can be made at different levels of granularity. In this work, we focus on making decisions at "two levels": whole problems vs. single steps and explore three types of granularity: "problem-level only" ("Prob-Only"),…

Complexity and difficulty are two closely related but distinct concepts. These concepts are important in the development of intelligent learning systems, e.g., for sequencing items, student modeling, or content management. We show how to use complexity and difficulty measures in the development of learning systems and provide guidance on how to…

The appeal of a shorter testing time makes a computer adaptive testing approach highly desirable for use in multiple assessment and learning contexts. However, for those who have been tasked with designing, configuring, and deploying adaptive tests for operational use at scale, preparing an adaptive test is anything but simple. The process often…

Although an increasing number of ethical data science and AI courses is available, with many focusing specifically on technology and computer ethics, pedagogical approaches employed in these courses rely exclusively on texts rather than on algorithmic development or data analysis. In this paper we recount a recent experience in developing and…

With the rapid rise of Artificial Intelligence in Education (AIEd), multiple stakeholders are questioning AI's capability to make fair and trustworthy decisions that improve teaching and learning. We suspect that unfair and unreliable outcomes might stem from lack of systematic collaboration between the developers of AIEd systems and the educators…

Online education platforms play an increasingly important role in mediating the success of individuals' careers. Therefore, while building overlying content recommendation services, it becomes essential to guarantee that learners are provided with equal recommended learning opportunities, according to the platform principles, context, and…

The increasing popularity of digital textbooks as a new learning media has resulted in a growing interest in developing a new generation of "adaptive textbooks" that can help readers to learn better through adapting to the readers' learning goals and the current state of knowledge. These adaptive textbooks are most frequently powered by…

300,000 immigrants move to Canada each year in search of better economic opportunities, and many have limited English language skills. Improving written literacy of newcomers can enhance education, employment, or social integration opportunities. However, frequent, timely, and personalized feedback is not always possible for immigrants. Online…