Skip to main content

Technology enhanced learning or learning driven by technology

David Baneres  1,2,  Denise Whitelock 3, Eric Ras 4, Abdulkadir Karadeniz 5Ana-Elena Guerrero-Roldán  1,2, M. Elena Rodríguez 1,2

Author details

1 D. Baneres, A.E Guerrero-Roldán and M.E. Rodríguez are with the Computer Science, Multimedia and Telecommunications Department, Universitat Oberta de Catalunya, Barcelona 08018, Rambla del Poblenou 156, Spain
2 D. Baneres, A.E Guerrero-Roldán and M.E. Rodríguez are with eLearn Center Department, Universitat Oberta de Catalunya, Barcelona 08018, Rambla del Poblenou 156, Spain. 
3 D. Whitelock is with Institute of Educational Technology, The Open University, Walton Hall, Milton Keynes, MK7 6AA, United Kingdom 
4 Eric Ras is with Luxembourg Institute of Science and Technology, 5 Avenue des Hauts-Fourneaux, L-4363 Esch-sur-Alzette, Luxembourg
5 A. Karadeniz is with Open Education Faculty, Anadolu University, Yunus Emre Campus, 26470, Eskisehir, Turkey


Students’ expectations have evolved during the last decade about how and when to study. Traditional teaching methodologies based on static material or master classes are not always the best approach to promote learning. Information and Communication Technologies (ICT) have been introduced to enhance the way the teaching process is undertaken. Utilizing ICT in education, or in other words, Technology Enhanced Learning (TEL), can facilitate efficient e-learning models where technology helps learners to build their knowledge and develop competencies. Online learning is continuously promoting new methodologies for learning by using technology as a cornerstone for this type of development and performance. Onsite teaching focuses on maintaining the interest of the learner by applying active learning or by moving to blended learning and using the technology as a new resource in the learning process. Thus, instructors and practitioners face revolutionary changes in teaching methodologies since the introduction of TEL. Technology is evolving incredibly fast, new trends are appearing and, also, the expectations of all actors (i.e., teachers and learners) are changing. TEL is helping to develop new teaching methodologies, yet technology is not the only resource to foster students’ knowledge. The intended technology should be examined based on the pedagogical necessity and integrated into education models. Because of this comprehension, this thematic series mainly focuses on disseminating learning experiences and critical studies enhanced by technology and not compelled by the use of technology. 


Technology Enhanced learning, active learning, e-assessment, pedagogical models, innovative teaching technologies. 


“If we teach today’s students as we taught yesterday’s, we rob them of tomorrow.”
-John Dewey-
The organization of instruction is a form that is built on previous practices and, it has a sustainability principle. According to Dewey quoted above, the instruction should aim the development of its own structure as well as it aims to the development of inputs after a certain period of time. This development will undoubtedly lead to better structuring as it is built on previous processes just like technology. The improvement in technology is similarly continuous, and the basic intention of technology is to advance human life. Considering that education is an imperative part of human life, we can imagine how significant the literal link between technology and education is. Therefore, we can state that advancement in technology has a reasonable impact on teaching manners and students learning, which are the basic inputs of the teaching and learning processes. It is perceived that the expectations of students have remarkably changed recently. Likewise, Rotherman and Willingham (2010) emphasize that a growing number of business leaders, politicians, and educators are united around the idea that students need “21st-century skills” to be successful today. Therefore, educational environments need to have better content, better teaching, and better tests and activities to enhance these skills. In order to suffice these expectations and to perform crucial learning experiences, various learning models, pedagogical approaches and technologies should be utilized.
E-learning appeared many years ago in a way totally different we face today. We can start explaining that the first e-learning course was by correspondence in 1840 by Isaac Pitman or the first testing machine in 1924, but for this thematic series, it is better to start in the digital era where delivery methods and tools were improved with web-based communication technologies. Gerstein (2014) defines this new era as Education 3.0 where “Education 3.0 recognizes that each educator's and student's journey is unique, personalized, and self-determined”. Other experts expect that education will change work contexts with the fourth industrial revolution (World Economic Forum, 2017). In any case, technology is playing a crucial role in this era and looking at the education as never has been seen before.
This change impacts all types of education levels, from elementary to higher education, but nowadays the impact in the economy and society is expected in higher education. Universities are preparing students for an uncertain future with new jobs needs, and they have to respond to this new challenge with the support of technology. Better learning environment spaces, better tools to communicate, better tools to practice skills, or better tools to support teacher’s work. These are some examples of where technology can impact. Thus, technology has not to be seen as a sustaining factor of the current learning methodologies, it has to be seen as a disruptive factor to reinforce the new economy and industry.   
This thematic series collects some advances in technology-enhanced learning related to higher education contexts. We tried to choose some relevant studies, where technology is used during the learning process. Also, selected papers where technology-enhanced environments with student-centered methodologies are compared with more traditional methodologies. Note that, this is a small selection of works for this topic. More relevant papers can be found within the journal or specific conferences on TEL such as the International Technology Enhanced Assessment Conference (TEA ). We invite the readers to visit those sources to read other relevant works. 
In order to introduce this special issue, we propose a review of the different topics of the thematic series and how technology is crucial on its development when learning is taking place. Section 2 introduces innovative teaching methodologies in Higher Education. Section 3 describes pedagogical models and theories underpinning technology-enhanced learning. Section 4 contains how technology helps on active learning, while Section 5 explains several innovations actions in assessment. 

Innovative teaching methodologies in higher education

Nowadays, teaching methodologies have been undoubtedly impacted by technology. Their evolution is not only by the technology intervention, but the need of involving students in the learning process (Chickering & Gamson, 1987). Teacher-centered approaches have evolved into student-centered ones. This has contributed to engaging student on the learning process and not only be “empty vessels who passively receive knowledge” (Lakoff & Johnson, 1980). Based on Weimer (2002), student-centered approaches “focus attention squarely on learning: what the student is learning, how the student is learning, the conditions under which the student is learning, whether the student is retaining and applying the learning, and how current learning positions the student for future learning”.
Based on the distinction between teacher- and student-centered approaches and based on technology use, teaching methodologies can be classified into four types. The less technological and teacher-centered approaches are traditional instruction in face-to-face learning environments. Here, direct instruction (Adams & Engelmann, 1996) can be found where the teaching strategy relies on explicit teaching through lectures; or kinesthetic (also known as hands-on) approach (Begel, Garcia & Wolfman, 2004) where students perform practical activities rather than listening to lectures. Technology helped to improve teacher-centered approaches. Flipped classroom (Bergmann, & Sams, 2012) is a clear example where technology helped to switch the teaching structure by leaving recorded lectures for homework and then, employing in-class time on performing assignments and promoting discussion. Although one may think the flipped classroom is a more student-centered approach, this method still relies on the idea of the teacher as the main authority figure. 
When we analyze student-centered approaches, there are also methodologies where technology is not mandatory to be used. An example is a differentiated instruction that Tomlinson (2005) defined as “a philosophy of teaching that is based on the premise that students learn best when their teachers accommodate the differences in their readiness levels, interests and learning profiles”. Thus, this instruction is a student-centered approach that provides students with different resources, activities, and learning processes based on their needs according to teacher evaluation. Another example is expeditionary instruction (Klein & Riordan, 2011) commonly used in schools or professional development where students go to expeditions and consequently they are engaged in an in-depth study of topics that impact their knowledge. 
Focusing on the utilization of technology, we can find inquiry-based instruction (Edelson, Gordin, & Pea, 1999) where students acquire knowledge through finding information, resources and asking questions. Here the teacher’s role changes to be a facilitator that guides students throughout their learning process. Note that here, technology is a valuable asset when seeking information or presenting the findings as videos, websites or presentations. 
Another approach is personalized learning. We can define it as an evolution of the differentiate learning with the main difference that it is the learner who decides what and how to learn. The United States National Education Technology Plan (2017) defined personalized learning as “instruction in which the pace of learning and the instructional approach are optimized for the needs of each learner. Learning objectives, instructional approaches, and instructional content (and its sequencing) may all vary based on learner needs”. Technology is relevant to facilitate the instruction as Pogorskiy (2015) stated as “ICT and communications technology can be a powerful tool for personalized learning as it allows learners access to research and information, and provides a mechanism for communication, debate, and recording learning achievements”.
Finally, game-based learning (Prensky, 2003) is also another student-centered approach which also requires high use of the technology to provide the environment to learn. Students learn through games by solving exercises or solving problems. Engagement is enhanced by using game-based techniques such badges, achievements, and quests, among others. 
In this scope, we propose two case studies. The first one is “Comparison of pharmacy students randomized to receive drug information reference education via recording or interactive Moodle lesson” by Wisniewski & Hortman (Wisniewski & Hortman, 2019). It is a comparison of traditional direct instruction with personalized learning instruction with Moodle. Authors showed a considerable improvement in retention on learners who learned by the online lectures. The second case study is “Enhancing students’ written production in English through flipped lessons and simulations” by Angelini & García-Carbonell (Angelini & García-Carbonell, 2019). Authors evaluated the learning process based on web-based simulations with a flipped classroom approach for learning a foreign language. The evaluation demonstrates the effectiveness of such combination in the student’s written production.
3.    Pedagogical models and theories underpinning Technology Enhanced Learning
When technology met learning, some authors found that technology was not innovating the learning process, but learning processes were technologized. Ravenscroft (2001) claimed that “the industry was technology-led rather than theory-led (the e-learning)”. Similarly, Nichols (2003) was concerned about e-learning conceptualization and claimed that “It is unlikely that e-learning practice will continue to evolve unless the theoretical underpinnings of e-learning are explored and debated”.
Some authors put effort into defining new theoretical frameworks to support e-learning based on pre-existent learning theories. A relevant work can be found in Anderson & Dron (2011) where the combination of traditional models was analyzed in distance learning supported by technology. 
Note that, those models helped to create new pedagogical models. Some of those models appeared when technology was capable to support them. One example is open learning. D’Antoni (2007) defined “Open and distance learning seeks to make education more open to those who need or wish for alternative opportunities to the traditional system”. With the support of the technology, open learning was accessible for the citizens by the use of web-based communication technologies and creating spaces such as MOOCs platforms (Pappano, 2012), and elaborating free resources such as open educational resources - OER (Atkins, Brown, & Hammond, 2007).
Another example is learning communities (also known as communities of practice) where learners who have some common academic goals, join to advance in their acquisition of knowledge. This is not a new concept. Smith (1993) defined “the learning community approach fundamentally restructures the curriculum, and the time and space of students. […] learning community models intentionally link together courses or coursework to provide greater curricular coherence, more opportunities for active teaming, and interaction between students and faculty”. Technology (Dede, 2004) has helped to create large learning communities previously limited by time and space constraints by using web-based, synchronous and asynchronous technological tools. 
A variant of the previous one is a knowledge building community where the main goal is not the acquisition of knowledge but its construction. The first conception appears in the nineties in Scardamalia & Bereiter’ (1994) work where authors proposed this type of communities to foster learning with the utilization of nineties technology (e.g., CD-ROM). However, similar to the learning communities, the knowledge building communities have increased in size and relevance with web-based communication technologies. A clear example is Wikipedia (Korfiatis, Poulos & Bokos, 2006). 
In this scope, we present two case studies. The first case study entitled “Promoting open educational resources based blended learning” by Sandanayake (Sandanayake, 2019), proposes an evaluation on Open Educational Resources (OER) in a blended setting. The study shows the effectiveness of their utilization in performance and opinion. The second case study namely “Persuasive Technology for Enhanced Learning Behavior in Higher Education” by Widyasari, Nugroho, & Permanasari, (Widyasari, Nugroho, & Permanasari, 2019) is related to the application of persuasive technology. As stated by Mintz & Aagaard (2010), persuasive technology is built from behaviorism pedagogical model, social-cultural theory and cognitive psychology. We consider this case study interesting to analyze how such systems can impact on the behavior of the learner. 
4.    Active learning methodologies
Across the years, technology also enhanced active learning methodologies. These techniques were initially proposed in the eighties due to the urge of involving students in the learning process. Chickering & Gamson (1987) suggested that “students must do more rather than just listen: They must read, write, discuss, or be engaged in solving problems. Most important, to be actively involved, students must engage in such higher-order thinking tasks as analysis, synthesis, and evaluation”. Following this statement, Bonwell & Eison (1991) defined active learning as “any instructional method that engages students in the learning process. In short, active learning requires students to do meaningful learning activities and think about what they are doing”.
Many traditional strategies have been defined to better engage students in classrooms. Prince (2004) summarized those strategies as two core elements of active learning: Introducing the student activity during a traditional lecture and promoting student engagement. Many works empirically supported the effectiveness of these core elements (Ruhl, Hughes, & Schloss, 1987; Hake, 1999; Laws, Sokoloff, & Thornton, 1999; Wankat, 2002).
With the irruption of technology on education, supporting active learning has been easier in all educational contexts. In traditional contexts, computer-equipped classrooms fostered active learning. Note that, it differs from computer-assisted classrooms as Holbert, Karady (2009) stated, “A computer-assisted classroom is defined as that having a single computer for instructor use only, whereas a computer-based classroom provides each student or pair of students with a computer”. The computer-equipped classrooms help instructors and learners to collaboratively work by, for instance, sharing solved exercises (Simon, Anderson, Hoyer, & Su, 2004), meanwhile the latter promotes simply an exhibition of prepared slides. 
In online context, technology has generated new ways of delivering education. Learners are able to practice and acquire skills. Sophisticated online games have been developed to foster collaborative communication skills, creativity, and critical thinking. Some examples can be found in different knowledge areas like nutrition (Mellecker, Witherspoon & Watterson, 2013), medical (Telner, Bujas-Bobanovic, Chan, et al., 2010), or nursing (Boctor, 2013) among others. Augmented reality and virtual worlds are also substituting the real fieldwork. In this regard, taking a virtual role helps to build empathy and a better understanding. Some examples can be found in aerospace design (Okutsu, DeLaurentis, Brophy, & Lambert, 2013), architecture engineering construction (Rahimian, Arciszewski, & Goulding, 2014) or chemistry laboratory (Ali, Ullah, Alam, & Rafique, 2014), among others.  
Within this scope, we propose the paper “Integration of good practices of active methodologies with the reuse of student-generated content” by Arruabarrena, Sánchez, Blanco, Vadillo, & Usandizaga (Arruabarrena, Sánchez, Blanco, Vadillo, & Usandizaga, 2019). It proposes a list of good practices related to active learning methodologies and they have been tested in a qualitative manner in different subjects in higher education. 
5.    Assessment and Evaluation in Technology Enhanced Learning
One great contribution of technology is the one related to assessment or better denoted as “e-assessment”. Guàrdia, Crisp and Alsina (2017) defined e-assessment as “the use of ICT to facilitate the entire assessment process, from designing and delivering assignments to marking, […] reporting, storing the results and/or conducting the statistical analysis”.

Technology offers new opportunities for assessment. The learning process can be more student-centered and activities can be even providing practice for complex cognitive skills to prepare students for the professional world (Crisp, 2009). There are several technologies for enhancing assessment: multi-choice test (Bull & McKenna, 2004; Conole & Warburton, 2005; Jordan, 2012), rubric-based (Dornisch & McLoughlin, 2006), peer review (Loddington, Pond, Wilkinson, & Willmot, 2009; Barbera ,2009), e-portfolios (JISC, 2008; Whitelock, 2010), among others. 

However, sometimes there is some misunderstandings about the potential of the application of technology in e-assessment. As it is mentioned by the European Commission (2012) e-assessment brings an added value. Adopting e-assessment involves much more than introducing online technologies into the assessment process; it means supporting effective learning. In JISC 2010, the same conclusion is highlighted: “Effective assessment and feedback can be defined as practice that equips learners to study and perform to their best advantage in the complex disciplinary fields of their choice, and to progress with confidence and skill as lifelong learners, without adding to the assessment burden on academic staff. Technology [...] offers considerable potential for the achievement of these aims”.

This leaves us with the question of how assessment with feedback can assist students to perform to their best advantage?  Digital feedback is moving forward more quickly with the advent of learning analytics.  Data can now be collected unobtrusively and during learning activities.  However, collecting more student data does not necessarily mean that it can provide “just in time” good teaching guidance. It is the latter which is advocated by Whitelock (2011) who suggests good feedback provides “Advice for Action” to the student.  Tutors can be assisted to give this type of feedback using OpenMentor (Whitelock et al., 2012b), an open source system that analyses tutor feedback.  One of the problems which students experience with tutor feedback is that socio-emotive support can be neglected while only cognitive feedback is supplied by the tutor.  More importantly, the feedback also needs to be relevant to the assigned grade (as demonstrated by Whitelock, Watt, Raw & Moreale, 2004).

With OpenMentor feedback is not seen as error correction but as part of the dialogue between student and tutor.  This is important since thinking of students making errors is unhelpful and as Norman (1988) points out, errors are better thought of as approximations to correct action. Therefore, tutor feedback should move the student in the right direction.

In order to provide feedback OpenMentor has first to analyze the tutor comments on an assignment and classify them into a number of categories.  The system then compares the categories used by the tutor with the mark they have awarded to the student.  The classification system used in OpenMentor was based on that of Bales (1950). Bales’ model provides four main categories of integration: positive reactions, negative reactions, questions and answers.

OpenMentor has been used in anger by Southampton University and Kings College London (Whitelock et al, 2012a; 2012b) and it has had a positive effect on tutors’ feedback practice.  Marking students’ work is always a challenge but we need to maintain our empathy with the learner.  Tools like OpenMentor can assist with prompting tutors to provide both emotional support and conceptual guidance but how can we ensure that the feedback is given to the student who actually wrote and submitted the given assignment?

E-Assessment is also capable of enforcing authentication and authorship in education. Online monitoring, also known as proctoring systems, simulates face-to-face assessment in virtual environments. Companies such as Kryterion  or ProctorU  offer this type of systems. Learners can perform an e-assessment activity while they are monitored through webcam. However, scalability depends on the infrastructure and number of proctors the company is able to provide. Other companies, such as Safe Exam Browser ( or Secure Exam (, proposed a more automated proctoring. Here, the system creates a controlled environment on the learner’s computer by blocking undesirable applications and connections to online resources and monitoring all the actions performed by the learner. Those systems are highly intrusive, and sometimes the learner may feel anxiety due to the security constraints to perform the assessment activities. Here the personal data regulation plays an important role.
However, other methodologies have recently appeared. They are focusing on being less intrusive by applying technologies previously applied in other areas such as banking or security. An example is the TeSLA system (Peytcheva-Forsyth, 2017) where biometric recognition and plagiarism methods have been integrated into a unique environment. Keystroke detection (Peacock, Ke, & Wilkerson, 2004; Choraś & Mroczkowski, 2007), forensic analysis (Koppel & Winter, 2014; García- Gorrostieta, López-López, & González-López, 2018), face recognition (Sinha, Balas, Ostrovsky, & Russell, 2006), voice recognition (Kinnunen, Karpov, & Franti, 2006) and plagiarism detection (Alzahrani, Salim & Abraham, 2012) can be deployed during an e-assessment activity to check the identity and the authorship of the learner. 
6.    Concluding Remarks 
Presently, technology has become an integral part of our daily lives. In such a state, education cannot be expected to settle in traditional ways. As in every area, education must continue its transformation with the support of technology. When this transformation commences occurring correctly, we can say that the learning process will be affected positively. Technology-enhanced learning environments not only promote the transfer of content but also support to use strong e-assessment methods. These environments are directed towards active participation of teachers and students and interaction between them. The usage of technology-enhanced learning environments contributes students to develop analytical thinking and problem-solving skills. It also facilitates teachers to follow the learner status, organize the feedback system, and monitor her own situation.
In this paper, we have presented the benefits of using technology into the education of the digital era, but also separately the benefits on different aspects of the education. The change is unavoidable, educational landscape is changing, and it is being adapted to the society new needs. The effects were foreseen some years ago, but nobody knows how the change will be complete. We will observe this shaping, and the teachers and the learners will play an important role.  


This work is partially supported by the European Union (H2020-ICT-2015) through the TeSLA project (An adaptive Trust-based e-assessment System for Learning). Number 688520 and the eLearn Center at Universitat Oberta de Catalunya through the project: New Goals 2018NG001 "LIS: Learning Intelligent System”.
Also, we would like to thank the Technology-enhanced knowledge and interaction group (TEKING) research group at Universitat Oberta de Catalunya for its support on completing this editorial due to its expertise on technology-enhanced learning, e-assessment processes, knowledge technologies and their application in the knowledge society.


Adams, G. L., & Engelmann, S. (1996). Research on Direct Instruction: 25 Years beyond DISTAR. Educational Achievement Systems, 319 Nickerson Street, Suite 112, Seattle, WA 98109.

Ali, N., Ullah, S., Alam, A., & Rafique, J. (2014). 3D interactive virtual chemistry laboratory for simulation of high school experiments. Proceedings of EURASIA GRAPHICS.

Alzahrani, S. M., Salim, N., & Abraham, A. (2012). Understanding plagiarism linguistic patterns, textual features, and detection methods. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 42(2), 133-149.

Anderson, T., & Dron, J. (2011). Three generations of distance education pedagogy. The International Review of Research in Open and Distributed Learning, 12(3), 80-97.

Angelini, M.L, & García-Carbonell. A. (2019). Enhancing students’ written production in English through flipped lessons and simulations. International Journal of Educational Technology in Higher Education, 16(1).

Arruabarrena, R., Sánchez, A., Blanco, J.M., Vadillo, J.A., & Usandizaga, I. (2019). Integration of good practices of active methodologies with the reuse of student-generated content. International Journal of Educational Technology in Higher Education, 16(1).

Atkins, D. E., Brown, J. S., & Hammond, A. L. (2007). A review of the open educational resources (OER) movement: Achievements, challenges, and new opportunities (pp. 1-84). Mountain View: Creative common.

Bales, R.F (1950) A set of categories for the analysis of small group interaction. American Sociological Review, 15:257-63
Barbera, E. (2009). Mutual feedback in e‐portfolio assessment: an approach to the netfolio system. British Journal of Educational Technology, 40(2), 342-357.

Begel, A., Garcia, D. D., & Wolfman, S. A. (2004). Kinesthetic learning in the classroom. ACM SIGCSE Bulletin, 36(1), 183.

Bergmann, J., & Sams, A. (2012). Flip your classroom: Reach every student in every class every day. International society for technology in education.

Boctor, L. (2013). Active-learning strategies: The use of a game to reinforce learning in nursing education. A case study. Nurse education in practice, 13(2), 96-100.
Bonwell, C. C., & Eison, J. A. (1991). Active Learning: Creating Excitement in the Classroom. 1991 ASHE-ERIC Higher Education Reports. ERIC Clearinghouse on Higher Education, The George Washington University, One Dupont Circle, Suite 630, Washington, DC 20036-1183.
Bull, J. and Danson, M. (2004) Computer-aided assessment (CAA). York: LTSN Generic Centre.
Chickering, A. W., & Gamson, Z. F. (1987). Seven principles for good practice in undergraduate education. AAHE bulletin, 3, 7.
Choraś, M., & Mroczkowski, P. (2007). Recognizing individual typing patterns Pattern
Recognition and Image Analysis (pp. 323-330): Springer.
Conole, G., & Warburton, B. (2005). A review of computer-assisted assessment. Research in Learning Technology, 13(1), 17-21.
Crisp, G. T. (2009). Towards authentic e-assessment tasks. In G. Siemens, & C. Fulford (Eds.). Proceedings of EdMedia: World conference on educational media and Technology 2009 (pp. 1585–1590). Association for the Advancement of Computing in Education (AACE).

D’Antoni, S. (2009) Open Educational Resources: reviewing initiatives and issues, Open Learning: The Journal of Open, Distance and e-Learning, 24:1, 3-10,

Dede, C. (2004). Enabling distributed learning communities via emerging technologies--Part One. The Journal, 32(2).

Dornisch, M. M. & McLoughlin, A. S. (2006). Limitations of web-based rubric resources: Addressing the challenges. Practical Assessment Research & Evaluation, 11(3). Available online:

Duval, E., Sharples, M., & Sutherland, R. (2017). Research themes in technology enhanced learning. In Technology Enhanced Learning (pp. 1-10). Springer, Cham.
Edelson, D. C., Gordin, D. N., & Pea, R. D. (1999). Addressing the challenges of inquiry-based learning through technology and curriculum design. Journal of the learning sciences, 8(3-4), 391-450.
European Commission (2012). Assessment of key competences in initial education and training: Policy guidance. Commission Staff Working Document. Retrieved from

García‐Gorrostieta, J. M., López‐López, A., & González‐López, S. (2018). Automatic argument assessment of final project reports of computer engineering students. Computer Applications in Engineering Education, 26(5), 1217-1226.
Gerstein, J. (2014). Moving from education 1.0 through education 2.0 towards education 3.0. Available at: Last Accessed: 20/03/2019. 

Guàrdia, L., Crisp, G., & Alsina, I. (2017). Trends and challenges of e-assessment to enhance student learning in higher education. In E. Cano, & G. Ion (Eds.). Innovative practices for higher education assessment and measurement (pp. 36–56). USA: IGI Global.

Hake, R. R. (1999). Interactive-engagement vs. traditional methods: A six-thousand student survey of mechanics test data for introductory physics courses.[En línea]. Department of Physics, Indiana University, Bloomington, Indiana 47405.

Holbert, K. E., & Karady, G. G. (2009). Strategies, challenges and prospects for active learning in the computer-based classroom. IEEE transactions on education, 52(1), 31-38.

JISC. (2008). Effective Practice with e-Portfolios. Bristol: JISC.

JISC (2010) Effective assessment in a digital age: a guide to technology-enhanced assessment and feedback. Available at (accessed 14 March 2019).

Jordan, S. (2012) Student engagement with assessment and feedback: some lessons from short-answer free-text e-assessment questions, Computers & Education 58 (2), 818–834.

Kinnunen, T., Karpov, E., & Franti, P. (2006). Real-time speaker identification and verification IEEE Transactions on Audio, Speech, and Language Processing (Vol. 14, pp. 277-288).

Klein, E. J., & Riordan, M. (2011). Wearing the “student hat”: Experiential professional development in expeditionary learning schools. Journal of Experiential Education, 34(1), 35-54.

Koppel, M., & Winter, Y. (2014). Determining if two documents are written by the same author. Journal of the Association for Information Science and Technology, 65(1), 178-187.

Korfiatis, N. T., Poulos, M., & Bokos, G. (2006). Evaluating authoritative sources using social networks: An insight from Wikipedia. Online Information Review,30, 252–262.

Lakoff, G., & Johnson, M. (1980).Metaphors we live by. Chicago, IL:University of Chicago Press.

Laws, P., Sokoloff, D., & Thornton, R. (1999). Promoting active learning using the results of physics education research. UniServe Science News, 13, 14-19.

Loddington, S., Pond, K., Wilkinson, N., & Willmot, P. (2009). A case study of the development of WebPA: An online peer‐moderated marking tool. British Journal of Educational Technology, 40(2), 329-341.

Mellecker, R. R., Witherspoon, L., & Watterson, T. (2013). Active learning: Educational experiences enhanced through technology-driven active game play. The Journal of Educational Research, 106(5), 352-359.

Mintz, J., & Aagaard, M. (2010). The Application of Persuasive Technology to educational settings: Some theoretical from the HANDS Project. In P. Hasle, T. Plough, H. Oinas-Kukkonen, & T. Räisänen (Eds.), Persuasive 2010, Proceedings of Poster Papers for the Fifth International Conference on Persuasive Technology Oulu: Oulu University Press.  University of Oulu.

Nichols, M. (2003) A Theory for e-Learning. Educational Technology and Society, 6(2), 1-10.

Norman, D. (1988). The psychology of everyday things. New York: Basic Books.

Okutsu, M., DeLaurentis, D., Brophy, S., & Lambert, J. (2013). Teaching an aerospace engineering design course via virtual worlds: A comparative assessment of learning outcomes. Computers & Education, 60(1), 288-298.

Pappano, L. (2012). The Year of the MOOC. The New York Times, 2(12), 2012.

Peacock, A., Ke, X., & Wilkerson, M. (2004). Typing patterns: A key to user identification. IEEE Security & Privacy, 2(5), 40-47.

Peytcheva-Forsyth, R. (2017). Opportunities and challenges for e-assessment: The contribution of the TeSLA project to improving trust in e-assessment. In e-ASEM conference in Copenhagen.

Pogorskiy, E. (2015). Using personalisation to improve the effectiveness of global educational projects. E-learning and Digital Media, 12(1), 57-67.

Prensky, M. (2003). Digital game-based learning. Computers in Entertainment (CIE), 1(1), 21-21.

Prince, M. (2004). Does active learning work? A review of the research. Journal of engineering education, 93(3), 223-231.

Rahimian, F., P., Arciszewski, T., & Goulding, J., S. (2014) Successful education for AEC professionals: case study of applying immersive game-like virtual reality interfaces, Visualization in Engineering, 2(1), p. 4.

Ravenscroft, A. (2001) Designing e-Learning Interactions in the 21st Century: revisiting and rethinking the role of theory. European Journal of Education, 36(2), 133-156.

Reimagining the Role of Technology in Education: 2017 National Education Technology Plan Update". Available at: Accessed 19 March 2019.

Rotherman, A. J., & Willingham, D. T. (2010). 21st century skills” not new but a worthy challenge. American Educator, 17-20.
Ruhl, K. L., Hughes, C. A., & Schloss, P. J. (1987). Using the pause procedure to enhance lecture recall. Teacher education and special education, 10(1), 14-18.
Sandanayake, T.C. (2019). Promoting open educational resources-based blended learning. International Journal of Educational Technology in Higher Education, 16(1).
Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. The journal of the learning sciences, 3(3), 265-283.

Simon, B., Anderson, R., Hoyer, C., & Su, J. (2004). Preliminary experiences with a tablet PC based system to support active learning in computer science courses. ACM SIGCSE Bulletin, 36(3), 213-217.

Sinha, P., Balas, B., Ostrovsky, Y., & Russell, R. (2006). Face recognition by humans:
Nineteen results all computer vision researchers should know about. Proceedings of the IEEE, 94(11), 1948-1962.

Smith, B. L. (1993). Creating Learning Communities. Liberal Education, 79(4), 32-39.

Telner, D., Bujas-Bobanovic, M., Chan, D., Chester, B., Marlow, B., Meuser, J., Rothman, A. & Harvey, B. (2010). Game-based versus traditional case-based learning: comparing effectiveness in stroke continuing medical education. Canadian Family Physician, 56(9), e345-e351.
Tomlinson, C. A. (2005). Grading and differentiation: Paradox or good practice? Theory into Practice, 44(3), 262-269.

Wankat, P. C. (2002). The effective, efficient professor: Teaching, scholarship, and service (pp. 107-112). Boston, MA: Allyn and Bacon.
Weimer, M. (2002). Learner-centered teaching: Five key changes to practice. John Wiley & Sons.
Widyasari, Y.D.L.,2 Nugroho, L.E., Permanasari, A.E., (2019). Persuasive Technology for Enhanced Learning Behavior in Higher Education. International Journal of Educational Technology in Higher Education, 16(1).

Whitelock, D., Watt, S. N. K., Raw, Y., & Moreale, E. (2004). Analysing tutor feedback to students: first steps towards constructing an electronic monitoring system. ALT-J, 1(3), 31-42.

Whitelock, D. (2011). Activating Assessment for Learning: are we on the way with Web 2.0? In M. J. W. Lee & C.McLough (Eds.), Web 2.0-Based-E-Learning: Applying Social Informatics for Tertiary Teaching (pp. 319-342): IGI Global.

Whitelock, D.M., Gilbert, L., Hatzipanagos, S., Watt, S., Zhang, P., Gillary, P. & Recio, A. (2012a). Addressing the Challenges of Assessment and Feedback in Higher Education: A collaborative effort across three UK Universities. In Proceedings INTED 2012, Valencia, Spain. ISBN: 978-84-615-5563-5

Whitelock, D., Gilbert, L., Hatzipanagos, S., Watt, S., Zhang, P., Gillary, P. Recio, A. (2012b). Assessment for Learning: Supporting Tutors with their Feedback using an electronic system that can be used across the Higher Education sector, In Proceedings 10th International Conference on Computer Based Learning in Science, CBLIS 2012, 26-29 June, Barcelona, Spain. 

Wisniewski, C.S, & Hortman, M.B. (2019). Comparison of pharmacy students randomized to receive drug information reference education via recording or interactive Moodle lesson. International Journal of Educational Technology in Higher Education, 16(1).

World Economic Forum. (2017). Accelerating Workforce Reskilling for the Fourth Industrial Revolution: An agenda for Leaders to Shape the Future of Education, Gender and Work. World Economic Forum, Geneva, Switzerland.

Associated institutions

The International Journal of Educational Technology in Higher Education is associated with:

Universitat Oberta de Catalunya

Universidad de los Andes

Dublin City University

New Content Item

Annual Journal Metrics

  • 2022 Citation Impact
    8.6 - 2-year Impact Factor
    9.4 - 5-year Impact Factor
    3.850 - SNIP (Source Normalized Impact per Paper)
    2.051 - SJR (SCImago Journal Rank)

    2022 Speed
    9 days submission to first editorial decision for all manuscripts (Median)
    105 days submission to accept (Median)

    2022 Usage 
    9,858 Altmetric mentions 

This journal is indexed by

  • Scopus
  • Social Sciences Citation Index® (SSCI)
  • Journal Citation Reports/ Social Sciences Edition
  • Current Contents®/Social and Behavioral Sciences
  • ProQuest Central
  • Google Scholar
  • DOAJ