People need access to data. Individual students and job seekers, families, educators, communities, and policymakers must have the information they need to foster successful journeys through education and the workforce. Robust statewide longitudinal data systems (SLDSs) can be designed to prioritize meaningful access to data but must also protect…

This study aims to conduct a comparative study of Bagging and Boosting algorithms among ensemble methods and to compare the classification performance of TreeNet and Random Forest methods using these algorithms on the data extracted from ABIDE application in education. The main factor in choosing them for analyses is that they are Ensemble methods…

Many funding agencies require researchers to include a data management plan with their grant applications explaining how they intend to make the data generated from the research publicly accessible. University administration and campus service providers could potentially leverage the content of data management plans to facilitate compliance and…

This is the fourth annual evaluation report for the Sorted in Schools, Te whai hua -- kia ora programme, a financial literacy programme for secondary school students and akonga, led by Te Ara Ahunga Ora Retirement Commission. In 2023, the evaluation focused on collecting data about key programme goals and reporting on the proportion of schools and…

This research aims to design a helpful methodology for estimating universities' relative impact on students as a sustainability factor in higher education. To this end, the research methodology implemented a two-stage approach. The first stage involves the relative efficiency analysis of the study units using Fuzzy Data Envelopment Analysis. The…

Education has been considered a cornerstone for human and economic development. Although there is a national educational strategy in most countries, various implementations are at the state level. This paper studies academic efficiency at the primary and secondary levels and the human development dimensions -- long and healthy life, being…

Data-driven decision making (DDDM) is an important teaching practice that can positively influence student achievement by using assessment data to make instructional decisions. The problem is that teachers do not always use this practice. Teachers' perspectives of DDDM can influence their data use practices. This basic qualitative study was…

This study explored the experiences of school counselors utilizing peer-group supervision to assist in analyzing data to determine the effectiveness of interventions. The literature gap indicates that further research was needed regarding the relationship between appropriate supervision and its impact on school counselors' ability to analyze data.…

In this position paper, the authors lay out the imperative for equitable artificial intelligence (AI), highlighting the essential role of access-oriented institutions and calling on technology companies (both large and small), foundations, and local, state, and federal regulators to consult with the newly convened Complete College America Council…

The purpose of this review is to examine the current literature on incremental rehearsal (IR) to investigate whether IR is be considered an evidence-based practice, based on the quality indicators set forth by the Council for Exceptional Children (Cook et al., 2014). Burns et al. (2012) completed a meta-analysis to investigate the effectiveness…

Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work-integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal…

Background: Over the last 20 years, educational large-scale assessments have undergone dramatic changes moving away from simple paper-pencil assessments to innovative, technology-based assessments. This comprehensive switch has led to some rather technical improvements such as identifying early guessing or improving standardization. Objectives: At…

In education, machine learning (ML), especially deep learning (DL) in recent years, has been extensively used to improve both teaching and learning. Despite the rapid advancement of ML and its application in education, a few challenges remain to be addressed. In this thesis, in particular, we focus on two such challenges: (i) data scarcity and…

In recent years, a multitude of datasets of human-human conversations has been released for the main purpose of training conversational agents based on data-hungry artificial neural networks. In this paper, we argue that datasets of this sort represent a useful and underexplored source to validate, complement, and enhance cognitive studies on…

The increased adoption of online learning environments has resulted in the availability of vast amounts of educational log data, which raises questions that could be answered by a thorough and accurate examination of students' online learning behaviours. Event logs describe something that occurred on a platform and provide multiple dimensions that…