Relying on the nation's first judicial big data research base for people's courts in Southeast University, Southeast University Law School has set up a training direction for graduate students in legal big data and artificial intelligence, and explored the "three-dimensional, small-scale, wide-ranging, and large-scale ecology." The…

This paper seeks to empirically validate a sector agonistic instrument that measures the perceived critical success factors in data governance. Twelve constructs (Leadership and Management Commitment; Leadership and Management Alignment; Executive Sponsorship; Robust Data Governance Strategy; Change Management; Training and Education; Governance…

Businesses assess public sentiment toward relevant topics and gain valuable insights through social media analytics (SMA). Students of business information analytics can therefore reap multiple benefits from SMA as a learning tool. We designed and implemented an SMA capstone project that integrated undergraduate research and community engagement.…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

Secondary data analyses occur when new analyses are proposed for existing data. Although they are prevalent in special education research, there is little guidance on how to prepare secondary data analyses studies. Preregistration of secondary data analyses studies provides a nice opportunity and structure for fellow researchers to share…

When learning about scientific phenomena, students are expected to "mechanistically" explain how underlying interactions produce the observable phenomenon and "conceptually" connect the observed phenomenon to canonical scientific knowledge. This paper investigates how the integration of the complementary processes of designing…

Purpose: The purpose of this study is to analyze the integration of sustainable practices in the strategies and operations of world-class higher education institutions (HEIs) under the theoretical guidance of Max Weber's instrumental and value rationalities. Design/methodology/approach: The results of the Quacquarelli-Symonds World University…

Despite efforts to implement innovative approaches such as flipped learning leveraging computer technology, the challenge of student failure persists. Understanding the factors that contribute to student success in flipped engineering courses remains a critical issue. This study addresses this issue by investigating the impact of student…

Undergraduate research is considered to be a high-impact practice; however, research into the data literacy of students conducting undergraduate research is lacking. In addition, institutionwide assessments of data practices are challenging because of varied disciplinary approaches to data. This study investigates the data practices of…

Increasing investment and interest in research and development (R&D) requires an efficient management system for achieving better research project outputs. In tandem with this trend, there is a growing need to develop a method for predicting research project outputs. Motivated by this, using information gathered in the early stage of projects,…

Despite the promotion of data-driven or data-informed instructional practices in teacher education and professional development, past research indicates that teachers use a limited number of sources for student data to make short-term adjustments to their teaching in order to address deficiencies in student learning. Science teachers, with a more…

In science classrooms, students usually see and work with data that's intended to tell them right away about the natural world. Students then often treat the data we provide to them as factual, rather than as a source of evidence (Duschl 2008; Sandoval and Millwood 2005; Berland and Reiser 2009; McNeill and Berland 2017; Hancock, Kaput, and…

Web recommendation systems are ubiquitous in the world used to overcome the product overload on e-commerce websites. Among various filtering algorithms, Collaborative Filtering and Content Based Filtering are the best recommendation approaches. Being popular, these filtering approaches still suffer from various limitations such as Cold Start…

As data become more available and integrated into daily life, there has been growing interest in developing data science curricula for youth in conjunction with scientific practices and classroom technologies. However, the "what" and "how" of data science in pre-collegiate education have not yet reached consensus. This paper…