See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/261458150 Instructional strategies for teaching science online Conference Paper in Proceedings - Frontiers in Education Conference · October 2013 DOI: 10.1109/FIE.2013.6685081 CITATIONS READS 4 956 Some of the authors of this publication are also working on these related projects: STEM+C View project All content following this page was uploaded by Dazhi Yang on 08 September 2016. The user has requested enhancement of the downloaded file. Instructional Strategies for Teaching Science Online Dazhi Yang Department of Educational Technology Boise State University Boise, United States Abstract—This work in progress reports the design and initial implementation of a complete online statistics course. It focuses on applications and adaptations of effective instructional strategies based on current research and best practice of teaching quantitative oriented courses (math, statistics, and engineering) online. The online statistics course was an introductory course and covered common statistical concepts and their applications in educational research for graduate students in educational technology. The course was equivalent to an undergraduate level statistics class for students majoring in science, technology, math, and engineering (STEM). Thus the implications of this project in terms of effective instructional strategies and online course design are relevant to a board audience including course designers, instructors, and students in science and engineering. Keywords--teaching online; statistics; instructional strategies I. INTRODUCTION Online courses continue to grow unprecedentedly in higher education. According to the tenth annual survey released by the Sloan Consortium, more than 6.7 million students took at least one online course during the fall of 2011 [1]. In addition, thirty-two percent of postsecondary students took at least one course online in 2011. In practice, more instructors are teaching or will teach online courses. However, teaching online is fundamentally different from teaching in a face-to-face setting [2], [3]. Instructors teaching online find it more difficult and time-consuming to teach. It is even more difficult to teach science and other quantitative orientated courses completely online because these courses usually require more hands-on activities and live demonstrations [4]. Meanwhile more educators agree that quantitative orientated courses such as math and statistics can be effectively taught online despite of their application-based nature [4], [5]. However, little has been done in developing effective instructional strategies for teaching such courses online [4]. The research aspect of this project in addition to the design and implementation of an online course was to investigate student’s feedback and perspectives on the effectiveness of the instructional strategies and activities adopted in a complete online statistics course. This work in progress reports the design and initial implementation of a full online statistics course, focusing on 978-1-4673-5261-1/13/$31.00 ©2013 IEEE applications and adaptations of effective instructional strategies based on current research and best practice of teaching quantitative oriented courses online. The statistics course was intended for graduate students who were pursuing their masters’ degrees in the field of educational technology. The course covered common statistical concepts and their applications in educational research. It was equivalent to an undergraduate level statistics course for students majoring in STEM fields. II. INSTRUCTIONAL STRATEGIES ADOPTED There were not many studies on effective instructional strategies for teaching science online. Thus the author extended the literature review on effective instructional strategies and best practice for teaching science online to quantitative oriented courses which include math, statistics and engineering. Four main strategies are most frequently adopted and implemented: (1) promoting interactivity through asynchronous and synchronous communications or delivery [7] - [8], [2], (2) facilitating the applications of concepts using strategies such as problem-based learning [10], [12] ; (3) using video demonstrations (such as screencasts for demonstrating tools and programs) [13], [14], and (4) conveying a strong social presence or a sense of belonging to a learning community [17] - [18]. Main instructional strategies adopted in this online statistics course included: online discussion forum, video demonstrations of statistical tests and procedures in SPSS, case studies of published research articles, mini projects, learning module reflections. The course used Moodle (a learning management system) to host all the course content. Table 1 briefly summarizes the literature review and instructional strategies adopted in the course Interaction can be promoted through either synchronous or asynchronous communication modes. Synchronous communication involves real-time interaction such as instant messaging, chat rooms, and online office hours. They address concerns immediately [8] and are believed to be more effective than asynchronous delivery mode [9]. However, they are often not practical for students that have difficulty meeting at fixed times. Asynchronous communication allows students to have more flexibility and work at their own pace [8], [11]. A drawback to this approach is a delayed time response and difficulty in collaboration. Regardless of delivery modes, conveying a strong social presence is essential to connecting with students in online courses [17], [18]. This improves perceived instructor support [17] and promotes students' participation. Effective teaching strategies also include the use of problem-based learning [11], case studies [3], and video demonstrations [13], [14]. Although time consuming and challenging to implement online, these methods promote engagement, help students construct their own knowledge [5], [3], and enhance teaching statistical software packages [15]. III. PRELIMINARY RESULTS The preliminary analysis of all students’ reflections submitted for six modules of the course indicated that all instructional strategies adopted were effective. Due to the page limit, we will not discuss details of the results. This online course will be redesigned based on the student’s feedback (reflections) on the initial implementation and will also be incorporated with some mobile learning components during the summer of 2013. The mobile learning components include but are not limited to the following: allowing course website accessible via smart phones and iPads; incorporating some components for motivating and alleviating students’ fear and anxiety toward learning statistics; incorporating some content-based Apps. for students to manipulate some difficult concepts, such as types of errors. The redesigned course will be offered again in Fall 2013. Video demonstrations [13], [14] Social presence [17], [18] How to achieve? Pros & Cons Interactivity, [6], [7], [2] Synchronous communication/delivery mode [8], [9] •Instant message through course website •Chat rooms •Office hours provided • Pros: More effective than textbased asynchronous delivery mode [9]; Enables students to be active & collaborative learners [7]; Promote higher level cognitive skills [7], [2]; Address concerns immediately, and immerse in problem-solving and decision-making processes [8]; • Cons: Cost more for equipment; Not practical –meet in fixed time/travel [11] • Pros: Enables students to be active & collaborative learners [6] -[7], [2]; Work at their own pace, offers greater flexibility and have more time to reflect on their learning [8], [11]; • Cons: Unsatisfied with instructors’ responses at a delayed time [5]; Unease of collaborating [5] Asynchronous communication/delivery mode [8], [12] •Online discussion forum •emails Applications of concepts [10], [12] •Problem-based learning (PBL) [11] •Case studies [3] •Case studies •Mini projects • Pros: Increase engagement [5], [3]; Help students construct their own statistical knowledge [5], [3]; Allows students to play a more proactive role in their learning [3]; Pros: Improve perceived instructor support [17]; Promote students’ participation in learning activities; REFERENCES [1] [2] TABLE 1. EFFECTIVE INSTRUCTIONAL STRATEGIES REVIEWED AND ADOPTED Strategies/ activities •Different tools/programs •Existing videos from Internet •Screencasts •Introduction videos •Video introduction & instructor profile [16], [19] •Discussion forum •Different communication channels [20] •Video introduction & instructor profile •Discussion forum •Different communication channels • Cons: Time consuming to prepare; Not easily implemented in online • Pros: Enhance teaching statistical software packages online [15]; Cons: Length limit and should only contain the right amount of information [11], [16] [3] [4] [5] [6] [7] [8] E. Allen, & J. Seaman, “Changing Course: Ten Years of Tracking Online Education in the United States”, retrieved from http://sloanconsortium.org/publications/survey/changing _course_2012, 2012. K. S. Davis, W. & Snyder, “Fostering science education in an online environment: Are we there yet?”, Journal of College Science and Teaching, 42, 2012, pp. 24-31. A. A. Juan, C. Steegmann, A. Huertas, M. A. Martinez, & J. Simosa, “Teaching mathematics online in the European Area of Higher Education: An instructor’s point of view”, International Journal of Mathematical Education in Science and Technology, 42, 2011, pp. 141153. O. Akdemir, “Teaching math online: Current practices in Turkey”, Journal of Educational Technology Systems, 39, 2010, pp. 47-64. J. J. Summers, A. Waigandt, & T. Whittaker, “A comparison of student achievement and satisfaction in an online versus a traditional face-to-face statistics class”, Innovative Higher Education, 29, 2005, pp. 233-250. M. G. Moore, “Editorial: Three types of interaction”, American Journal of Distance Education, 3(2), 1989, pp. 1-7. D. Lawton, N. Vye, J. Bransford, E. Sanders, M. Richey, D. French, & R. Stephens, “Online learning based on essential concepts and formative assessment”, Journal of Engineering Education, 101, 2012, 244-287. H-Y. Ku, C. Akarasriworn, D. M. Glassmeyer, B. Mendoza, L. A. Rice, “Teaching an online graduate mathematics education course for in-service mathematics teachers”, Quarterly Review of Distance Education, 12, 2011, pp. 135-147. [9] M. P. Myers & P. M. Schiltz, “Use of elluminate in online teaching of statistics in the health sciences”, Journal of Research in Innovative Teaching, 5, 2012, pp. 53-62. [10] D. K. Strang, “Skype synchronous interaction effectiveness in a quantitative management science course”, Decision Sciences Journal of Innovative Education, 10, 2012, pp. 3-23. [11] X. Huan, R. Sheshane, & A. Ali, “Teaching computer science courses in distance learning”, Journal of Instructional Pedagogies, 6, 2011, pp. 1-14. [12] M. V. Steinberg, “Teaching introductory statistics and probability online in a pace format: Some best practices”, Journal of Research in Innovative Teaching, 3, 2010, pp. 193-202. [13] I. Gemmell, J. Sandars, S. Taylor, & K. Reeda, “Teaching science and technology via online distance learning: the experience of teaching biostatistics in an online Master of Public Health programme”, Open Learning, 26(2), 2011, pp. 165–171. [14] S. A. Ariadurai & R. Manohanthan, “Instructional strategies in teaching engineering at a distance: Faculty perspective”, International Review of Research in Open and Distance Learning, 9, 2008, pp. 1-11. [15] A. AlAsfour, “Examining student satisfaction of online statistics courses. Journal of College Teaching & Learning”, 9, 2012, pp. 33-38. [16] S. T. Miller & S. L. Redman., “Enhancing student performance in an online introductory astronomy course with video demonstrations”, Astronomy Education Review, 9, 2010, pp. 010114-1-010114-9. [17] J. Zhang & R. T. Walls, “Instructors’ self-perceived pedagogical principle implementation in the online environment”, The Quarterly Reivew of Distance Education, 7, 2006, pp. 413-426. [18] D. Thomas, L. Qing., L. Knott, L. Zhongxiao, “The structure of student dialogue in web-assisted mathematics courses”, Journal of Educational Technology Systems, 36, 2007, pp. 415-431. [19] C. Kim & C. Hodges, “Effects of an emotion control treatment on academic emotions, motivation and achievement in an online mathematics course”, Instructional Science, 40, 2012, pp. 173-192. [20] R. Majeski & M. Stover, “Theoretically based pedagogical strategies leading to deep learning in asynchronous online gerontology courses”, Educational Gerontology, 33, 2007, pp. 171-185. View publication stats