Advances in Teaching and Learning Minitrack

Permanent URI for this collectionhttps://hdl.handle.net/10125/42273

The Advances in Teaching and Learning Technologies minitrack encourages research contributions that deal with learning theories, cognition, tools and their development, enabling platforms, communication media, distance learning, supporting infrastructures, user experiences, research methods, social impacts, and/or measurable outcomes as they relate to the area of technology and its support of improving teaching and learning. Appropriate usage environments range from same-time, same-place to anytime, anywhere that increase interactions among the learners and the teacher/facilitator. Special interest continues to focus on innovative ways of using social media to facilitate learning and its application to early childhood education. This mini-track is intended to include all aspects of teaching and learning technologies from the original inceptions of theories and tools through the measurement of learning outcomes.

Minitrack Co-Chairs:

David H. Spencer (Primary Contact)
New Jersey Institute of Technology
Email: dspencer@njit.edu

Timothy Ellis
Nova Southeastern University
Email: ellist@nova.edu

Eric Santanen
Bucknell University
Email: esantane@bucknell.edu

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Now showing 1 - 15 of 15

Using Journals to Assess Non-STEM Student Learning in STEM Courses: A Case Study in Cybersecurity Education
(2017-01-04) Kessler, Gary; Dardick, Glenn; Holton, Douglas
Embry-Riddle Aeronautical University offers a \ minor course of study in cybersecurity as an option in \ our undergraduate Homeland Security program. \ Since the students are, by and large, social scientists, \ the focus of the program is to build hyper-awareness \ of how cybersecurity integrates within their \ professional aspirations rather than to provide \ cybersecurity career-level proficiency. Assessing \ student learning of the technical aspects cannot be \ performed using traditional tests, as they would not \ properly measure what the students are learning in a \ practical sense. Instead, we employ journals and self-reflection \ to ask the students to express and \ demonstrate their learning. Although somewhat \ harder to grade, the journals have huge benefits to \ the learning environment as well as to actual \ learning.
Towards a Sentiment Analyzing Discussion-board
(2017-01-04) Thoms, Brian; Eryilmaz, Evren; Mercado, Glo; Ramirez, Benjamin; Rodriguez, Jose
In this paper we present the design and construction of a sentiment analyzing discussion board, which was used to support learning and interaction within an existing online social networking (OSN) system. More specifically, this research introduces an innovative extension to learning management software (LMS) that combines real-time sentiment analysis with the goal of fostering student engagement and course community. In this study we perform data mining to extract sentiment on over 6,000 historical discussion board posts. This initial data was analyzed for sentiment and interaction patterns and used for guiding the redesign of an existing asynchronous online discussion board (AOD). The redesign incorporates a sentiment analyzer, which allows users to analyze the sentiment of their individual contributions prior to submission. Preliminary results found that the proposed system produced more favorable outcomes when compared to existing AOD software.
Task-technology Fit Aware Expectation-confirmation Model towards Understanding of MOOCs Continued Usage Intention
(2017-01-04) Ouyang, Yuanxin; Tang, Cui; Rong, Wenge; Zhang, Long; Yin, Chuantao; Xiong, Zhang
Massive Open Online Courses (MOOCs) have been playing a pivotal role among the latest e-learning initiative and obtain widespread popularity in many universities. But the low course completion rate and the high midway dropout rate of students have puzzled some researchers and designers of MOOCs. Therefore, it is important to explore the factors affecting students’ continuance intention to use MOOCs. This study integrates task-technology fit which can explain how the characteristics of task and technology affect the outcome of technology utilization into expectation-confirmation model to analyze the factors influencing students’ keeping using MOOCs and the relationships of constructs in the model, then it will also extend our understandings of continuance intention about MOOCs. We analyze and study 234 respondents, and results reveal that perceived usefulness, satisfaction and task-technology fit are important precedents of the intention to continue using MOOCs. Researchers and designers of MOOCs may obtain further insight in continuance intention about MOOCs.
Social Media in Educational Practice: Faculty Present and Future Use of Social Media in Teaching
(2017-01-04) Esteve Del Valle, Marc; Gruzd, Anatoliy; Haythornthwaite, Caroline; Paulin, Drew; Gilbert, Sarah
This paper presents results from a questionnaire (n=333) designed to gain an understanding of instructor motivations and experience with social media use in educational practice. Data on overall use of social media, and instructors’ use of social media in classes are applied to assess factors leading to present and future use of social media in teaching, using a framework based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) model. Our findings show use in teaching is driven by factors associated with UTAUT’s Performance Expectancy construct, i.e., personal engagement with social media, and Moderating Condition of age, with older participants making greater use of social media in teaching. Other constructs associated with use are Habit (experience teaching online), Social Influence (colleagues using social media), Effort Expectancy (awareness of barriers, staying informed), Facilitating Conditions (institutional technology support) and Moderating Conditions (teaching at a two-year college).
Reducing Computer Anxiety in Self-Paced Technology Training
(2017-01-04) Gupta, Saurabh
Industry reports continue to highlight the importance and growth of e-learning. However, researcher, trainers and trainees all agree that e-learning is different in terms of the level of personalization and anxiety that it brings, and its impact on outcomes. This paper presents a research model to reframe the dominant theory in technology training, i.e. Socio-Cognitive theory and its impact on learning, including the impact of perceived anxiety and team-based learning. Results from an empirical study are presented. Results show that teams based e-learning can reduce perceived anxiety and thus, improve training outcomes. Theoretical and practical implications are also presented.
Reaching beyond the Classroom through the Use of Push Notifications
(2017-01-04) Kallookaran, Michael; Robra-Bissantz, Susanne
New technologies enable educators to modify their \ teaching methods and extend their reach beyond the \ classroom. One of these methods that can be applied to \ communicate with students is through the use of push \ notifications on smartphones. Instead of relying on \ students to use a spaced learning approach, which is \ proven to be more efficient than trying to study \ something in a short period of time, it is now possible \ to remind them to learn and stick to a learning \ schedule from day one. For this research we \ implemented a mobile application that enables \ students to subscribe to a course and get push \ notifications on their smartphone if new questions are \ being made available by the teacher. The experiment \ we conducted shows that students who use push \ notifications are returning more often to the \ application and better stick to a given learning \ schedule than students who don’t have push enabled.
Promotion of Educational Effectiveness by Translation-based Programming Language Learning Using Java and Swift
(2017-01-04) LI, Juhua; Sakamoto, Kazunori; Washizaki, Hironori; Fukazawa, Yoshiaki
More and more programming tools have been created to help people to learn new programming languages. Although the number of tools to support beginning learners has increased, none directly compare different languages. This paper proposes a translation-based programming learning method that supports programming language learning for beginners of a new language who are familiar with a different language. Comparing the same code written in the two languages allows learners to discover commonalities and differences between the two languages, understand grammar rules, and successfully write programs in the new language. Our method is demonstrated using a web-based educational environment that translates Java into Swift. An experiment to evaluate the educational effectiveness confirms that using a programming language educational environment with translation support can aid beginning learners in learning a new programming language.
Prediction Method based DRSA to Improve the Individual Knowledge Appropriation in a Collaborative Learning Environment: Case of MOOCs
(2017-01-04) Bouzayane, Sarra; Saad, Inès
This paper proposes a prediction method that relies on the Dominance-based Rough Set Approach (DRSA) to improve the individual knowledge appropriation when the learning process occurs in a collaborative environment such as the Massive Open Online Courses (MOOCs). This method is based on two phases: the first has to be applied at the end of each week of the MOOC and aims at inferring a preference model resulting in a set of decision rules; the second is applied at the beginning of each week of the same MOOC and consists of classifying each learner in one of the three defined decision classes, which are Cl1 of the “At-risk Learners”, Cl2 of the \ “Struggling Learners” and Cl3 of the “Leader Learners”, based on the previously inferred preference model. This method runs weekly. It has \ been validated on real data of a French MOOC proposed by a Business School in France.
Optimizing Usability Testing in the Context of a Large-scale Software Service for Digital Textbooks
(2017-01-04) Kastner, Margit; Simon, Bernd
The adoption of digital textbooks in education has steadily increased. This paper reports on the initiative Digi4School aiming to provide a large-scale software service for digital textbooks. Since the usability of this service is of particular concern, it is the subject of a design science research project with the goal to investigate two artifacts: (1) an optimized method for usability testing and (2) a fully-functional software service for delivering digital textbooks to users with heterogeneous IT background. We conclude that a combination of usability tests and the use of a questionnaire including closed and open-ended questions is recommended. Furthermore, both novice and expert users should evaluate a system’s usability with iterations until the usability measures reach a satisfactory level for all users. This was achieved for Digi4School. Such an approach has the potential to identify and eliminate flaws that prevent users from adopting the system.
Microcore: A Playable Case Study for Improving Adolescents’ Argumentative Writing in a Workplace Context
(2017-01-04) Balzotti, Jonathan; Hansen, Derek; Ebeling, Daniel; Fine, Lauren
A playable case study is an immersive, transmedia story controlled by a puppetmaster (i.e., teacher), but played by participants who advance the plot through their contributions and interactions with fictional characters. They are also explicitly educational, consisting of both the immersive, transmedia story, as well as in-game and out-of-game materials provided for educational scaffolding and reflection. We present the Microcore playable case study to illustrate the potential of this new type of experiential simulation that incorporates aspects of Alternate Reality Games (ARGs) to increase immersion. We present results from a pilot test of Microcore with an undergraduate course, identifying design strategies that worked well and others that led to improvements that are currently being incorporated. We also provide questions to prompt future designers of playable case studies and discuss our findings in a broader context of educational simulations. \
Knowledge Management for Learning: ICT System Affordances and the Impact of Order of Use
(2017-01-04) Collins, Regina; Hiltz, Starr Roxanne; Deek, Fadi
Knowledge management (KM) is an important activity in corporations and organizations and is well suited as a learning activity in higher education. However, integrating such activities for learning requires alignment between required activities and information technology (IT) system affordances. Using KM-based assignments requiring individual and collaborative (group) Internet-based research, this study explores the affordances of two different ITs: one the university’s learning management system, and the other a Web 2.0 social digital curation system (Pearltrees). Results suggest that, despite already being familiar with Moodle, students found Pearltrees not complex and generally compatible with their learning activities, although their perceptions were impacted by whether they used Pearltrees for the first or second assignment. Students’ comments indicated that mature discussion capabilities and a visual interface with the ability to organize digital resources were some of the most important affordances for tools used in KM learning activities.
Does Applying Screenshot Annotations Enhance Learning Effectiveness? The Moderating Role of Course Difficulty
(2017-01-04) Huang, Travis K.; Huang, Eugenia
The rapid growth of information technologies has given rise to a variety of e-learning platforms. However, simply providing multimedia instructional materials does not necessarily improve users’ understanding of the instructional content. The study makes use of Flickr annotations, including stickers, drawings, and texts, to improve users’ learning performance while learning computer software. All users are able to upload screenshots to Flickr to demonstrate computer software problems and troubleshooting software. To clarify what their screenshots mean, they can describe their problems or provide their opinions by attaching annotations to a specific screenshot. Through the use of annotations, Flickr provides the users with an easier way to describe or understand problems. This study comprised a three-course investigation. In addition to understand users’ learning effectiveness, two context-related factors, peer opinion and personal innovativeness, were chosen as the basis for the research model. Based on data collected from 281 students, the results indicated that peer opinion had a positive effect on intention, whereas the effect of personal innovativeness, surprisingly, was negative rather than positive. Besides, the results based on the three computer software courses with different levels of difficulty confirmed the moderating effect of course difficulty.
Computer Skill Acquisition: The Effects of Computer-aided Self-explanation on Knowledge Retention and Transfer
(2017-01-04) Chi, Tai-Yin; Olfman, Lorne; Berger, Dale E.
We conducted an experimental study to determine to what extent computer skill learners can benefit from generating self-explanation with the aid of different computer-based visualization technologies. Self-explanation was stimulated with dynamic visualization (Screencast), static visualization (Screenshot), or verbal instructions only, and compared to a control group with no self-explanation instructions. Sixty-two subjects were assigned to these four conditions for learning HTML fundamentals. Two quizzes were used to test learning outcomes. In comparison to the control condition, performance was best with dynamic visualization and static visualization. The self-explanation condition without visualization did not attain statistical significance in comparison to the control condition. Qualitative data collected from a learning experience survey regarding the subjects’ opinions about self-explanation prompts showed that subjects in different treatment groups gave similar responses about how they benefited from self-explanation prompts for learning HTML.
Blending Machine and Human Learning Processes
(2017-01-04) Crowston, Kevin; Østerlund, Carsten; Lee, Tae Kyoung
Citizen science projects face a dilemma in relying on contributions from volunteers to achieve their scientific goals: providing volunteers with explicit training might increase the quality of contributions, but at the cost of losing the work done by newcomers during the training period, which for many is the only work they will contribute to the project. Based on research in cognitive science on how humans learn to classify images, we have designed an approach to use machine learning to guide the presentation of tasks to newcomers that help them more quickly learn how to do the image classification task while still contributing to the work of the project. A Bayesian model for tracking volunteer learning is presented.
Introduction to Advances in Teaching and Learning Technologies Minitrack
(2017-01-04) Spencer, David; Ellis, Timothy; Santanen, Eric

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