Peer assessment has proven to be a useful strategy for increasing the timeliness and quantity of formative feedback, as well as for promoting metacognitive thinking among students. Previous research has determined that reviews that contain suggestions can motivate students to revise and improve their work. This paper describes a method for…

Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…

Policymakers have expressed increased interest in program-level higher education accountability measures as a supplement to, or in place of, institution-level metrics. But it is unclear what these measures should look like. In this report, we assess the ways program-level data could be developed to facilitate federal accountability. Evidence shows…

Purpose: This paper aims to introduce the extended qualitative content analysis (EQCA) method to integrate data-reducing and data-complicating research steps when conducting qualitative research on the United Nations and other international institutions. Design/methodology/approach: EQCA supplements the method of qualitative content analysis,…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…

The purpose of this study is to evaluate how learning disabilities (LDs), in combination with accommodations, affect the performance of a decision-tree to predict the stability of academic behaviour of undergraduate engineering students. Additionally, this study presents several examples to illustrate how a college could use the resultant model to…

The article shows the role of data mining methods at the stages of the e-learning risk management for the various participants. The article proves the e-learning system fundamentally contains heterogeneous information, for its processing it is not enough to use the methods of mathematical analysis but it is necessary to apply the new educational…

In secure web application development, the role of web services will not continue if it is not trustworthy. Retaining customers with applications is one of the major challenges if the services are not reliable and trustworthy. This article proposes a trust evaluation and decision model where the authors have defined indirect attribute, trust,…

Online learning has attracted a large number of participants and is increasingly becoming very popular. However, the completion rates for online learning are notoriously low. Further, unlike traditional education systems, teachers, if any, are unable to comprehensively evaluate the learning gain of each student through the online learning…

Data science is a broad, interdisciplinary field concerned with the extraction of knowledge or insights from data, with the classification of data as a core, fundamental task. One of the most persistent challenges faced when performing classification is the class imbalance problem. Class imbalance refers to when the frequency with which each class…

There are good reasons for higher education institutions to use learning analytics to risk-screen students. Institutions can use learning analytics to better predict which students are at greater risk of dropping out or failing, and use the statistics to treat "risky" students differently. This paper analyses this practice using…

Database files and additional log files of Learning Management Systems (LMSs) contain an enormous volume of data which usually remain unexploited. A new methodology is proposed in order to analyse these data both on the level of both the courses and the learners. Specifically, "regression analysis" is proposed as a first step in the…

This study explored the impact of partial credit scoring of one type of innovative items (multiple-response items) in a computerized adaptive version of a large-scale licensure pretest and operational test settings. The impacts of partial credit scoring on the estimation of the ability parameters and classification decisions in operational test…

Background: Since the discontinuation of Standard Attainment Tests (SATs) in science at age 11 in England, pupil performance data in science reported to the UK government by each primary school has relied largely on teacher assessment undertaken in the classroom. Purpose: The process by which teachers are making these judgements has been unclear,…