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We model international short-term capital flow by identifying technical trading rules in short-term capital markets using Genetic Programming (GP). The simulation results suggest that the international short-term markets was quite efficient during the period of 1997–2002, with most GP generated trading strategies recommending buy-and-hold on one or two assets. The out-of-sample performance of GP trading strategies varies from year to year. However, many of the strategies are able to forecast Taiwan stock market down time and avoid making futile investment. Investigation of Automatically Defined Functions shows that they do not give advantages or disadvantages to the GP results.

This chapter presents innovative approaches to active learning that were introduced into the teaching of preservice teachers at the Faculty of Education of University of West Bohemia, Pilsen, in the Czech Republic. Over the last three years, the Technology-Enhanced Learning course has seen substantial innovations in both the content and use of teaching strategies designed to prepare the students for their professional lives. The whole update of the course was implemented using the results of action research – all individual changes were rigorously tracked and analyzed. The state of the art in the active learning domain in education of preservice teachers is presented in this chapter.

There is a description of the procedure to update the course, based on the reflections of teachers and feedback from students, gathered during action research. Detailed evaluations of particular methods of active learning that have been proven in teaching are provided.

Besides practical activities with tablets and smartphones, during which students familiarize themselves with various types of applications and reflect on their use in teaching, the course was extended by the use of practical aids for the efficient inclusion of mobile technologies for teaching – the Czech version of Allan Carrington’s Padagogy Wheel. This aid is derived from the revised Bloom’s taxonomy and SAMR model and helps the systematic reflection of preservice teachers when preparing for technology-enhanced teaching.

A significant part of the teaching consists of cooperative projects between preservice teachers and pupils of elementary schools – for example, the preservice teachers help elementary school pupils discover possibilities of virtual reality during Google Cardboard activities, or preservice teachers in teams with elementary school pupils create digital stories together on the topic of Internet safety.

The innovative approach to active teaching in the Technology-Enhanced Learning course is apparent even during the exam. In the course of the exam, students process, present, and defend a lesson plan for the implementation of an activity using digital technologies.

Throughout the learning, as well as at the end, preservice teachers are encouraged to reflect on the teaching in the Technology-Enhanced Learning subject.

Purpose — Describe the system set-up and processing requirements for a long-duration longitudinal Global Positioning System (GPS)/prompted-recall (PR) survey conducted in Sydney, Australia and assess reaction and cognition of participants.

Design/methodology/approach — The survey uses data collected using an in-car GPS device within a PR interface accessed over the Internet by participants. Technical requirements, interface design and survey administration of the survey are discussed. This is followed by an assessment of participant burden and cognition by analysing user activity on the PR and comparing participant responses to information inferred from the GPS data.

Findings — New technologies have allowed for increasingly sophisticated data collection efforts but they require substantial resources to translate this into a usable form. This study shows these technologies can be used to conduct long-duration travel studies in a way that is appealing and engaging to participants. However, it was found that responses to the PR are sometimes inconsistent and caution should be drawn in taking PR responses as the ‘ground truth’.

Research limitations/implications — The relatively low participant burden of this study shows long-duration studies are feasible if care is taken to limit the work required by participants. The inconsistency of the responses to the PR suggest future surveys may need to employ mechanisms that are better able to aid participants in accurately completing the survey.

Originality/value — Details the requirements of running a long-duration GPS/PR survey and assesses participant burden and cognition of the survey which are often not reported.

Every “structural model” is defined by the set of covariance and mean expectations. These expectations are the source of parameter estimates, fit statistics, and substantive interpretation. The recent chapter by Cortina, Pant, and Smith-Darden ((this volume). In: F. Dansereau & F. J. Yammarino (Eds), Research in multi-level issues (vol. 4). Oxford, England: Elsevier) shows how a formal investigation of the data covariance matrix of longitudinal data can lead to an improved understanding of the estimates of covariance terms among linear growth models. The investigations presented by Cortina et al. (this volume) are reasonable and potentially informative for researchers using linear change growth models. However, it is quite common for behavioral researchers to consider more complex models, in which case a variety of more complex techniques for the calculation of expectations will be needed. In this chapter we demonstrate how available computer programs, such as Maple, can be used to automatically create algebraic expectations for the means and the covariances of every structural model. The examples presented here can be used for a latent growth model of any complexity, including linear and nonlinear processes, and any number of longitudinal measurements.

The application of blockchain, particularly through avenues in teaching and learning and academic administration, has created scope for a new business model in higher education. Although higher education institutions in many African countries including Botswana are yet to adopt blockchain in their institutional processes, the chapter points to seven unique areas of practice in which the technology could be infused. Distributed ledgers and smart contracts are among the blockchain functions that could assist in improving efficiency, security, and privacy in the way academic administration is executed especially in student identification, processing of student admission applications, degree certification, document authentication, and quality assurance. A distinct highpoint of the chapter is the attention it calls to student experience in the learning and teaching process, by highlighting that it stands to benefit from the collaborative learning model that blockchain enables. At a wider level, the conversation about blockchain-based pedagogy coalesces with the push by many African governments, in particular in Botswana, towards a digitally transformed society. Already, many colleges and universities have placed the focus on achieving ‘smart campuses’ as a strategic goal. Blockchain adoption is one such step towards a smart campus. The chapter theorises that higher education institutions cannot legitimately talk about smart campuses while still holding steadfast to manual systems and processes.