How can one understand the spread of ideas across text data? This is a key measurement problem in sociological inquiry, from the study of how interest groups shape media discourse, to the spread of policy across institutions, to the diffusion of organizational structures and institution themselves. To study how ideas and narratives diffuse across…

The Internet has transformed the way we read and the context in which we acquire knowledge. Online reading brings both unique opportunities and challenges. To utilize the full potential of this digital environment and to successfully participate in an online information society, digital reading skills are essential. But what makes online reading…

Generative AI (GenAI) is quickly becoming a valuable tool for sociological research. Already, sociologists employ GenAI for tasks like classifying text and simulating human agents. We point to another major use case: the extraction of structured information from unstructured text. Information Extraction (IE) is an established branch of Natural…

This article intends to empower and equip art educators to artistically address the functioning of facial detection algorithms through critical race theory (CRT). By highlighting how biometric data, a specific form of data that measures the physical qualities of individuals, is used in common social media facial detection algorithms like Snapchat,…

The objective of the paper was to outline the possibility of utilising information from online job postings and text-mining analyses to identify mismatches and gaps between learning outcomes prepared by universities, and the knowledge and skills that employers need. The study uses job advertisement contents and learning outcomes documents from…

We examined the impact of prospective information on the processing of information occurring within the present timeline of narrative stories. Participants read target sentences that were consistent with events occurring within a protagonist's present timeline but inconsistent with events in the protagonist's future. When prospective information…

The purpose of this hermeneutic phenomenology study was to understand Whole Brain Teaching (WBT) through the experiences and perceptions of teachers who utilize this system in the United States. The theory guiding this study was George Miller's information processing theory, which identified how information is attained, stored, and retrieved, a…

By assessing student engagement with learning tasks along with students' understanding of subject matter before and during teaching, teachers are able to shift their teaching approaches through improvisational pedagogical reasoning in real time. However, if a teacher does not know how to respond to students' cues, their capacity to effectively…

In today's digital world, higher education institutions collect and use more data than ever. However, institutional silos create barriers for stakeholders who need data for daily operations and strategy. This article presents a vision of a unified, collaborative future for data governance and actionable steps stakeholders can take.

Students need a strong understanding of how to represent chemical compounds in order to succeed in organic chemistry. This project set out to gain a better understanding of students' difficulties with symbolic representations, by identifying the specific errors associated with drawing wedge-dash structures. The focus was on how students…

Social identities impact the way individuals see themselves and their career options but career theories have been slow to the call in exploring how social identities interface with theoretical assumptions. The purpose of this study was to examine how social identities affect and inform specific dimensions identified by cognitive information…

Causal reasoning is a fundamental cognitive ability that enables individuals to learn about the complex interactions in the world around them. However, the mechanisms that underpin causal reasoning are not well understood. For example, it remains unresolved whether children's causal inferences are best explained by Bayesian inference or…

Graph Signal Processing (GSP) plays a crucial role in addressing the growing need for information processing across networks, especially in tasks like supervised classification. However, the success of GSP in such tasks hinges on accurately identifying the underlying relational structures, which are often not readily available and must be inferred…

In many teacher expectation studies, it is suggested that teachers can overcome expectation bias through enhanced "awareness." In this exploratory paper, I extrapolate and map the conceptual demarcations of 'teacher awareness' based on a thematic analysis of twenty-six teacher expectation studies identified in a systematic literature…

"Self-regulated learning" (SRL) significantly impacts the process and outcome of "programming problem-solving." Studies on SRL behavioural patterns of programming students based on trace data are limited in number and lack of coverage. In this study, hence, the Hidden Markov Model (HMM) was employed to probabilistically mine…