The Role of Visual Learning in Improving Students’ High-Order Thinking Skills

Various concepts have been introduced to improve students’ analytical thinking skills based on problem based learning (PBL). This paper introduces a new concept to increase student’s analytical thinking skills based on a visual learning strategy. Such a strategy has three fundamental components: a teacher, a student, and a learning process. The role of the teacher includes monitoring the learning process by considering the most productive way to improve higher-order thinking (HOT) skills.Many studies show that students learn from courses that provide information in a visual format. We introduce a meaningful learning strategy for the classroom that promotes the presentation of information in visual formats such as images, diagrams, flowcharts and interactive simulations.  Furthermore, we compared visual and traditional learners based on their HOT skills, which were evaluated using the SWOT model. Performance analysis shows that visual leaning tools increased the students’ HOT skills. Keywords: visual learning, PBL, HOT skills

Predicting the academic success of architecture students by pre-enrolment requirement: using machine-learning techniques

In recent years, there has been an increase in the number of applicants seeking admission into architecture programmes. As expected, prior academic performance (also referred to as pre-enrolment requirement) is a major factor considered during the process of selecting applicants. In the present study, machine learning models were used to predict academic success of architecture students based on information provided in prior academic performance. Two modeling techniques, namely K-nearest neighbour (k-NN) and linear discriminant analysis were applied in the study. It was found that K-nearest neighbour (k-NN) outperforms the linear discriminant analysis model in terms of accuracy. In addition, grades obtained in mathematics (at ordinary level examinations) had a significant impact on the academic success of undergraduate architecture students. This paper makes a modest contribution to the ongoing discussion on the relationship between prior academic performance and academic success of undergraduate students by evaluating this proposition. One of the issues that emerges from these findings is that prior academic performance can be used as a predictor of academic success in undergraduate architecture programmes. Overall, the developed k-NN model can serve as a valuable tool during the process of selecting new intakes into undergraduate architecture programmes in Nigeria

Spatio-temporal learning with the online finite and infinite echo-state Gaussian processes

Successful biological systems adapt to change. In this paper, we are principally concerned with adaptive systems that operate in environments where data arrives sequentially and is multivariate in nature, for example, sensory streams in robotic systems. We contribute two reservoir inspired methods: 1) the online echostate Gaussian process (OESGP) and 2) its infinite variant, the online infinite echostate Gaussian process (OIESGP) Both algorithms are iterative fixed-budget methods that learn from noisy time series. In particular, the OESGP combines the echo-state network with Bayesian online learning for Gaussian processes. Extending this to infinite reservoirs yields the OIESGP, which uses a novel recursive kernel with automatic relevance determination that enables spatial and temporal feature weighting. When fused with stochastic natural gradient descent, the kernel hyperparameters are iteratively adapted to better model the target system. Furthermore, insights into the underlying system can be gleamed from inspection of the resulting hyperparameters. Experiments on noisy benchmark problems (one-step prediction and system identification) demonstrate that our methods yield high accuracies relative to state-of-the-art methods, and standard kernels with sliding windows, particularly on problems with irrelevant dimensions. In addition, we describe two case studies in robotic learning-by-demonstration involving the Nao humanoid robot and the Assistive Robot Transport for Youngsters (ARTY) smart wheelchair

Toward Development Game-Based Adaptive Learning

Digital educational games have been used in schools for more than twenty years. Nowadays, digital educational games are being developed to serve goal-orient purposes.  This paper introduces ways to develop students’ HOT skills based on a structured approach to digital game-based adaptive learning (DGLA). The game approach in this study used a visual learning environment aimed at developing students’ HOT skills, which involve ordering, selecting, evaluating, contrasting, and comparing.  The Learning- based visual tools were designed to motivate primary school children and engage them in computer programming. Furthermore, we distributed a questionnaire to gauge the attitudes of students toward a learning game approach with a visual environment.  The questionnaire was focused on the categories of motivation and challenges. The results show a clear gap between pre and post- test in all categories. Keywords: HOT skills, game based learning, visual learning environmen

Squaring the circle: a new alternative to alternative-assessment

Many quality assurance systems rely on high-stakes assessment for course certification. Such methods are not as objective as they might appear; they can have detrimental effects on student motivation and may lack relevance to the needs of degree courses increasingly oriented to vocational utility. Alternative assessment methods can show greater formative and motivational value for students but are not well suited to the demands of course certification. The widespread use of virtual learning environments and electronic portfolios generates substantial learner activity data to enable new ways of monitoring and assessing students through Learning Analytics. These emerging practices have the potential to square the circle by generating objective, summative reports for course certification while at the same time providing formative assessment to personalise the student experience. This paper introduces conceptual models of assessment to explore how traditional reliance on numbers and grades might be displaced by new forms of evidence-intensive student profiling and engagement

Presenting Computer Science Concepts to High School Students

Computer science at high school often focusses on programming, but a broader view of other areas of computer science has key benefits for both writing programs that are more efficient and making more theoretical concepts more accessible to those who do not find programming intrinsically interesting. With the introduction of computer science at high schools, a lack of coherent resources for teachers and students prompted the development of the NZ Computer Science Field Guide, an open-source, on-line textbook. This paper describes the design of the Field Guide, which has fourteen chapters about various topics of computer science. The design includes written text, videos, classroom activities and interactive applications. The need for a broad view of computer science is discussed, and programming exercises to go with the topics are suggested

Cross-country Efficiency of Secondary Education Provision: a Semi-parametric Analysis with Nondiscretionary Inputs

We address the efficiency of expenditure in education provision by comparing the output (PISA results) from the educational system of 25, mostly OECD, countries with resources employed (teachers per student, time spent at school). We estimate a semi-parametric model of the education production process using a two-stage procedure. By regressing data envelopment analysis output scores on nondiscretionary variables, both using Tobit and a single and double bootstrap procedure, we show that inefficiency is strongly related to GDP per head and adult educational attainment.education; technical efficiency; DEA; bootstrap; semi-parametric

Cross-country efficiency of secondary education provision: a semi-parametric analysis with non-discretionary inputs

We address the efficiency of expenditure in education provision by comparing the output (PISA results) from the educational system of 25, mostly OECD, countries with resources employed (teachers per student, time spent at school). We estimate a semi-parametric model of the education production process using a two-stage procedure. By regressing data envelopment analysis output scores on nondiscretionary variables, both using Tobit and a single and double bootstrap procedure, we show that inefficiency is strongly related to GDP per head and adult educational attainment. JEL Classification: C14, C61, H52, I21Bootstrap, DEA, Education, semi-parametric, technical efficiency

Psychometrics in Practice at RCEC

A broad range of topics is dealt with in this volume: from combining the psychometric generalizability and item response theories to the ideas for an integrated formative use of data-driven decision making, assessment for learning and diagnostic testing. A number of chapters pay attention to computerized (adaptive) and classification testing. Other chapters treat the quality of testing in a general sense, but for topics like maintaining standards or the testing of writing ability, the quality of testing is dealt with more specifically.\ud All authors are connected to RCEC as researchers. They present one of their current research topics and provide some insight into the focus of RCEC. The selection of the topics and the editing intends that the book should be of special interest to educational researchers, psychometricians and practitioners in educational assessment