In higher education, e‑learning is gaining more and more impact, especially in the format of blended learning, and this new kind of traditional teaching and learning can be practiced in many ways. Several studies have compared face‑to‑face teaching to online learning and/or blended learning in order to try to define which of the formats provides, e.g., the highest learning outcome, creates the most satisfied students or has the highest rate of course completion. However, these studies often show that teaching and learning are influenced by more than teaching format alone. Many factors play significant roles, and this literature review will look further into some of them. The review has a special interest in professional bachelor education and teacher training, and it focusses on factors that influence learning experiences in e‑learning, online learning and blended learning. Thus, the research question of the review is as follows: Which factors are found to influence e‑learning and blended learning in relation to learning outcome, student satisfaction and engagement in collaboration in higher education and particularly in professional education? The findings from the research papers included in the review show that among the many factors some seem to dominate more: educator presence in online settings, interactions between students, teachers and content, and designed connections between online and offline activities as well as between campus‑related and practice‑related activities. The article thus points in the direction of some significant factors, but it also discusses and questions the relevance of research focusing on comparisons between individual formats of e‑learning, online learning, blended learning or "traditional" face‑to‑face teaching and learning. Teaching and learning are complex and are influenced by more than just the teaching format. The review is based on systematic database searches conducted in January 2017, and it includes 44 peer reviewed articles and papers published between 2014 and 2017.

As a number of recent studies suggest applications of networked computers in education have very inconsistent results ranging from success stories to complete failures. Literally, thousands of e‑learning projects have been carried out that greatly differ in their outcomes. Until now, however, there is no systematic or a standardized way of planning, comparing and evaluating e‑learning projects, their outcomes, and their effectiveness. Therefore, the main objective of this research was an investigation of possible approaches to systematic planning, development and evaluation of e‑learning initiatives and their corresponding e‑learning projects. The result of this work is a multidimensional model of e‑learning Indicators that are defined as the important concepts and factors that are used to communicate information about the level of e‑learning and used to make management decisions when planning e‑learning strategy. The lack of knowledge of the learner audience as well as of the factors influencing that audience and e‑learning projects overall results in failing to provide satisfactory support in the decision making process. In order to address this issue, an approach dealing with e‑learning indicators is proposed. Having a standardised guide of e‑learning indicators accepted by the scientific community enables comparison and evaluation of different initiatives regarding e‑learning in a standardised manner. The proposed E‑learning Indicators Methodology enables successful planning, comparison and evaluation of different e‑learning projects. It represents an empirical methodology that gives concrete results expressed through numbers that could be analysed and later used to compare and conclude its e‑learning efficiency. A practical value of this approach was analyzed in the realized comparative analyses of two different institutions using different LMS tools: Angel and Moodle focusing on comparison and evaluation of e‑learning indicators of these two e‑learning projects. With the application of this methodology in e‑learning projects it is more likely to achieve better results and higher efficiency as well as higher Return on Investment‑ROI.

Students often report feeling more overloaded in courses that use e‑learning environments compared to traditional face‑to‑face courses that do not use such environments. Discussions here consider online design and organizational factors that might contribute to students' reports of information overload. It was predicted that certain online factors might contribute to stimulus overload and possibly students' perceived overload, rather than information overload per se. User characteristics and a range of design and organizational factors that might contribute to perceived overload are discussed and hypotheses of how such factors might affect learning outcomes are also discussed. An experiment was conducted to test predictions that (i) students' past online experience, (ii) the organization and relevance of online information, and (iii) the level of task difficulty affect (i) learning outcomes, (ii) students' perceptions of information overload, and (iii) students' perceptions of having enough time to complete experimental tasks. A total of 187 participants were tested in four experimental conditions that manipulated the organization and relevance of online material that students had to learn (ie, (i) a stimulus‑low environment, where the material to be learned was presented as scrolling text, with no other stimuli present; (ii) a familiar environment, where the material to be learned was set within the borders of a familiar course Web site; (iii) a stimulus‑rich or stimulus‑ noisy environment, where the material to be learned was set within the borders of an Amazon.com Web page (a Web site where you can search for, and buy books, videos and other products online); (iv) a PDF file environment, where the material to be learned was presented as a PDF file that resembled an online duplicate of the same material in the course textbook). Findings suggested that overly busy online environments that contain irrelevant information (ie, stimulus‑rich or stimulus‑noisy online environment) had a negative impact on learning for students ranked "high" on experience with e‑learning technologies, but no impact on learning for other students (as measured by a knowledge test of material studied during experimental sessions). There is no doubt that online environments contain vast amounts of information and stimuli; often some of which are irrelevant and distracting. How one handles irrelevant or distracting information and stimuli can have a significant impact on learning. Surprisingly, results here suggest that overload affected only experienced students. Perceptual load hypotheses are discussed to explain what initially seemed to be counterintuitive results. This paper examines literature that considers factors that can affect learning online, strategies for how teachers can ensure positive outcomes for the technology‑based classroom, and strategies for avoiding online pitfalls that might leave students frustrated or burdened with feelings of overload.

Educational systems worldwide are being challenged to respond effectively to the digital revolution and its implications for learning in the 21st century. In the present new media age, educational reforms are desperately needed to support more open and flexible structures of on‑demand learning that equip students with competencies required in a globalized and multicultural world. Game‑based learning represents one pathway to educational reform through its emphasis on performance. In this paper we describe the Statecraft X game‑based learning program that blends performative game‑based learning with dialogic pedagogy in the context of citizenship education. The Statecraft X curriculum was designed with the understanding that a digital game on its own does not necessarily lead to meaningful student learning. Rather, it is the students together with their peers and aided by their teacher who must work together to make meaning of their in‑game experiences and connect these experiences to real‑world events and issues through thoughtful reflection. With a view to addressing widespread shortcomings of citizenship education that reduce the curriculum to learning about citizenship, the Statecraft X game, played on Apple iPhones, provides students with a first person experience of governance by allowing them to take on the role of governors and thus to enact governance. Central to the SCX program is its dialogic pedagogy where teachers facilitate meaningful conversations among students and advance their understanding of citizenship and governance. In this paper, we report an implementation of the Statecraft X curriculum in a Social Studies class attended by 42 15‑year‑olds attending a secondary school in Singapore. Students’ understanding of governance and citizenship was assessed by means of an essay that students attempted at the end of the program. Students’ performance in the essay was compared with a comparable control group taught the same topic by traditional method. The results indicate that students of the intervention class outperformed the control class students. Our findings suggest that the Statecraft X curriculum has efficacy in achieving the desired curricular learning outcomes. These findings have implications for school leaders, teachers, and students with respect to introducing and integrating game‑based learning in regular classrooms.

Abstract: This paper describes use of an online Student Response System (SRS) in a pre‑qualification course for engineering studies in Norway. The SRS in use, where students answer quizzes using handheld mobile devices like Smartphones, PADs, iPods etc., has been developed at Sør‑Trøndelag University College. The development of the SRS was co‑funded by the Lifelong Learning Program KA3‑ICT in 2009‑2010. SRS has been designed to help teachers effortlessly i) break the monotony of a lecture and allow the students to actively take part in the lecture, ii) increase teacher‑student interaction, and iii) give teacher and students immediate anonymous feedback on learning outcome. The response system was used in mathematics in two groups with different lecturers during two semesters in 2009‑2010. The pedagogical methods in use will be referred to as “Peer Instruction” and “Classic”. In each method the students will answer a multiple choice quiz using their mobile devices. In both cases the result of the quiz will immediately appear as a histogram on a screen in the classroom. The closing parts will also be identical. The lecturer then highlights the correct option in the histogram and explains why this option actually is the correct one. In the Peer Instruction method there will be an additional element. The first poll will be followed by a discussion in student groups, where the students are urged to defend their choice and convince their fellow students that their chosen option is the correct one. The discussion is then followed by a new individual voting session before the final results are shown and the closing part takes place. The paper will compare this method with the peer instruction method as described in existing literature. The learning outcome will be discussed according to interviews with students and the lecturers’ experiences from the classroom. In addition we will analyze students’ grades and test results in mathematics with respect to their expected level, based on previous achievements. We will present results showing that when students are arguing their point of view, they will have a stronger tendency to convince their fellow students when they themselves already have found the correct option in the quiz. Finally we will suggest pedagogical improvements for future use of response systems in mathematics. Input from lecturers and from students has already been used in the process of developing a new version of SRS, finished in January 2013.

Abstract: This paper explores the design of a blended learning environment in a transition from face‑to‑face and seeks to determine whether learner characteristics and background together with blended learning design elements are significant factors for l earning outcomes such as intrinsic motivation, satisfaction, knowledge construction and learning performance in blended learning. It is aimed at examining the learner characteristics and backgrounds such as age, gender, self‑regulation, attitudes, family and social support as well as the management of workload in blended learning. It is again to find out the levels of use and satisfaction with blended learning design features such as interactions, learning management system tools and resources, face‑to‑fa ce support and technology quality by learners. Students from three schools and one directorate were involved in a face‑to‑face set up in the first part of a seventeen week semester and in an online set up in the second part. They finally had a face‑to‑fac e at the end to review their work after which they took end of semester examinations. A questionnaire survey was administered to 270 respondents in this group to gather data on student characteristics and background, design features and three of the outco mes. The examination results were used as a measure of the performance variable in the learning outcomes. We applied the online self‑regulated learning questionnaire for data on students self‑regulation, the intrinsic motivation inventory for data on mot ivation and other self‑developed instruments to measure the other constructs. Descriptive statistics showed that the identified learner characteristics manifest strength for blended learning design and the learners involvement with design features was fo und to be high and satisfactory. ANOVA results showed no significant differences between age groups in performance and t‑test results showed no significant differences between male and female students. Regression analysis results showed learner attitudes as predictors of learner satisfaction and motivation while workload management is a significant predictor for learner satisfaction and knowledge construction. Among the design elements, regression results showed only learner interactions as significant pr edictors of knowledge construction and satisfaction. As a consequence, a number of learner characteristics and design features are seen to be important for blended learning design and the non‑significant ones remain a focus for future research.