Educational Technology for Teaching Economics - Where to Start and How to Grow?
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| Title: | Educational Technology for Teaching Economics - Where to Start and How to Grow? |
|---|---|
| Language: | English |
| Authors: | William L. Goffe |
| Source: | Journal of Economic Education. 2024 55(1):77-84. |
| Availability: | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Peer Reviewed: | Y |
| Page Count: | 8 |
| Publication Date: | 2024 |
| Document Type: | Journal Articles Reports - Descriptive |
| Descriptors: | Beginning Teachers, Economics Education, Educational Technology, Technological Literacy |
| DOI: | 10.1080/00220485.2023.2274026 |
| ISSN: | 0022-0485 2152-4068 |
| Abstract: | New economics instructors face numerous challenges when selecting technology for their courses. Because economists teach at a variety of institutions with diverse student bodies and since technology continues to evolve, this article focuses on general principles that novice instructors should consider when selecting technology for their courses. One principle is that technology should support "deliberate practice," which encompasses many types of active learning. Instructors should be aware of the various constraints they face, including the numerous cognitive challenges to effective teaching, limitations to their own "working memory," and potentially limited resources of their students and institutions. The "Substitution, Augmentation, Modification, Redefinition" (SAMR) framework is introduced to explain how technology might influence instruction. Finally, instructors should learn how to optimally use the technology they select. |
| Abstractor: | As Provided |
| Entry Date: | 2024 |
| Accession Number: | EJ1406468 |
| Database: | ERIC |
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| FullText | Links: – Type: pdflink Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwHKb0pERHq6cBmLKCz_deDnAAAA4zCB4AYJKoZIhvcNAQcGoIHSMIHPAgEAMIHJBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDIlZtqxK4jt2M6FVVwIBEICBmytjUNHI9rVX1cYY04NUNv1vRYVbmyX7RMQLLCECDFGp1BcwZl1ifmz7uMqyHWF6xBlOwF9QoWSQrg1nVJkA9XfCZBLlswou6RTgP2UmqJZJu-SiBxZ7-9hKmY901A1QwFBsbH_QFcdgSTEE63BhkzmPtduPwiEidlUhVfKvEaLNCCxUpUbCnD8xawGbvopZ-_2TYESrBDYyYzdd Text: Availability: 1 Value: <anid>AN0174338623;jmd01jan.24;2023Dec22.04:24;v2.2.500</anid> <title id="AN0174338623-1">Educational technology for teaching economics–Where to start and how to grow? </title> <p>New economics instructors face numerous challenges when selecting technology for their courses. Because economists teach at a variety of institutions with diverse student bodies and since technology continues to evolve, this article focuses on general principles that novice instructors should consider when selecting technology for their courses. One principle is that technology should support "deliberate practice," which encompasses many types of active learning. Instructors should be aware of the various constraints they face, including the numerous cognitive challenges to effective teaching, limitations to their own "working memory," and potentially limited resources of their students and institutions. The "Substitution, Augmentation, Modification, Redefinition" (SAMR) framework is introduced to explain how technology might influence instruction. Finally, instructors should learn how to optimally use the technology they select.</p> <p>Keywords: deliberate practice; novice instructor; technology</p> <p>New instructors face a bewildering array of choices and challenges when they begin their teaching career. They range from the mundane, like the best way to get to work, to vitally important, like how to teach. Unfortunately, many new instructors feel that they could use more teacher training (Allgood, Hoyt, and McGoldrick [<reflink idref="bib1" id="ref1">1</reflink>]). The articles in this symposium offer essential guidance for new instructors, and this one addresses how to select the appropriate technology for teaching. Moreover, the suggestions in this article support many of the ideas and teaching suggestions outlined in the other symposium articles.</p> <p>Technology choices involve many complicating factors. One is the growing number of "learning solutions" offered by ed-tech firms. Their growth has been triggered by falling computer hardware costs and increasingly capable software. Sometimes, their offerings have scant basis in what is known about how students learn (Mollenkamp [<reflink idref="bib23" id="ref2">23</reflink>]). Also, classes can be taught in different modalities: face-to-face, hybrid, remote synchronous, and remote asynchronous; each might well use different technologies. Further, optimal teaching technology is context-dependent—an instructor teaching at an institution that can supply technology to students in need will have the option to select different technologies than those available to an instructor at a poorly resourced institution that cannot ensure universal access. Thus, many instructors must be prepared for students whose access to technology varies. With these complications in mind, I provide a flexible and adaptable framework for new instructors to make wise technology choices given their context. Further, I provide a framework for selecting technology as instructors gain experience and as technology evolves.</p> <p>I begin by outlining a teaching model that frames the discussion of technology-related choices for economic instruction. Next comes a description of the many constraints that instructors face, followed by an explanation of the "SAMR" framework for using technology in teaching. The article continues with an illustration of the challenges of student-selected technology before concluding with some specific examples of future technology-related opportunities.</p> <hd id="AN0174338623-2">Teaching model</hd> <p>Before discussing technology, it is helpful to describe the model of teaching assumed in this article because it influences technology choices. It is essential to keep in mind that technology is chosen to support teaching and that technology is not selected for its own sake. Put another way, the goal of teaching is to achieve specific learning goals and not to introduce technology to students. The model used here begins with the observation that economists often say that they want their students to "think like economists." One implication of this point is that teaching should include a considerable amount of time where students practice their thinking with feedback from instructors to shape that thinking. Technological tools can facilitate these crucial elements of teaching and learning.</p> <p>The cognitive scientist K. Anders Ericsson studied how a specific type of practice leads to deep expertise. In studies of numerous disciplines, from chess to violin playing, he found that most followed what he coined as "deliberate practice."[<reflink idref="bib1" id="ref3">1</reflink>] Ericsson and Pool ([<reflink idref="bib13" id="ref4">13</reflink>], 99) define it as</p> <p></p> <ulist> <item> Attempting tasks just beyond current abilities.</item> <p></p> <item> Using one's full attention for the task at hand.</item> <p></p> <item> Providing timely and accurate feedback for the student.</item> <p></p> <item> Developing and elaborating "effective mental representations."</item> </ulist> <p>The last point is relatively subtle but essential. It involves students making connections between related topics and concepts. For example, besides principles students calculating elasticities, they would be asked to explain how different types of elasticities are similar and different from each other and how the relevant curves might look on a graph. Or, when teaching supply and demand, students are confronted with questions that directly target common errors (Staples et al. [<reflink idref="bib33" id="ref5">33</reflink>]). By making connections between related concepts and addressing common errors, learning is enhanced. Deliberate practice can be implemented in many ways, including cooperative learning (McGoldrick [<reflink idref="bib21" id="ref6">21</reflink>]), team-based learning (Ruder, Maier, and Simkins [<reflink idref="bib28" id="ref7">28</reflink>]), or with clicker questions (Boyle and Goffe [<reflink idref="bib5" id="ref8">5</reflink>]). No matter the implementation, care must be taken to craft questions for students in the framework of deliberate practice and to ensure that students receive extensive feedback.</p> <p>Selecting the appropriate way to implement deliberate practice depends upon many individual factors that are beyond the scope of this article, but regardless, technology choices should be made to robustly support deliberate practice. However, as described in Wieman and Gilbert ([<reflink idref="bib38" id="ref9">38</reflink>], 204), technology does not, in and of itself, constitute deliberate practice but rather plays a supporting role: "While technology can support this learning process [deliberate practice], current technology does not yet provide the extensive engagement, interactions, and timely targeted feedback provided in a well-run classroom."</p> <hd id="AN0174338623-3">SAMR framework of teaching technology</hd> <p>A particularly useful framework for understanding and selecting technology in teaching is SAMR (Smith [<reflink idref="bib31" id="ref10">31</reflink>]). There are a multitude of technologies an instructor might use in a course, so how might one make a selection? This model provides a framework. Each letter in the acronym illustrates a possible use of technology in teaching.</p> <p>The letter S in SAMR represents "substitution"—technology merely substitutes for a nontechnological solution. One example is using PowerPoint as a replacement for writing on an overhead. In the classroom, there is little substantive difference between writing text by hand and displaying text in PowerPoint. Another example of a substitution technology is placing handouts in a learning management system (LMS) as opposed to paper handouts—both put material in the hands of students. Because substitution technologies offer few advantages, little instructor effort should be spent on them if the nontechnological forms are already used. That is, if paper handouts work fine for one's class, continue to use them.</p> <p>The letter A in SAMR stands for "augmentation," where technology yields a functional improvement in teaching. One example is PowerPoint slides that might be saved online for students (which certainly aids those with accessibility issues). Another example of augmentation might be video recordings of a class, which enable students to replay a class meeting. As augmenting technologies can aid learning, they are worth consideration by an instructor.</p> <p>The letter M is for "modification," where technology deepens learning. One example is clicker technology, which allows students to vote on questions during class. As described in Levy, Yardley, and Zeckhauser ([<reflink idref="bib19" id="ref11">19</reflink>]), clickers give a more accurate reflection of student views than raising hands, as students tend to follow others when their hands go up. This suggests that this technology can deepen learning as the instructor has more accurate data on student knowledge. Clickers were once dedicated hand-held devices, but now they usually operate via software on phones or tablets. They enable think-pair-share (also known as Peer Instruction [Crouch and Mazur [<reflink idref="bib8" id="ref12">8</reflink>]]). With it, the instructor poses a challenging question, and students vote in privacy with their clickers. If a significant number of students miss the question (Crouch and Mazur suggest less than 70 percent), students are instructed to turn to their neighbor and convince each other of their answer. The class votes again, and typically, more students answer correctly. Finally, the instructor adds a further explanation of the correct answer to provide additional insight. If more than 70 percent of the students answer correctly, there is little need for students to confer with each other, but the instructor still explains the correct answer. Smith et al. ([<reflink idref="bib32" id="ref13">32</reflink>]) find that a combination of Peer Instruction and instructor explanation maximizes learning, which is consistent with deliberate practice. Another example of modification is online grading, such as with SpeedGrader in the Canvas LMS, which can speed up the grading process for instructors. Thus, augmenting technologies deserve serious consideration by instructors.</p> <p>The letter R in the SAMR model stands for "redefinition," where instruction requires technology. One example is teaching remotely via Zoom (which obviously became quite common during the pandemic), and another is online interactive videos, where students answer questions embedded in videos. If carefully done, such videos can enable further deliberate practice by students. Such redefinition technologies deserve serious consideration by instructors as they use technology to potentially improve learning.</p> <p>The SAMR framework enables instructors to consider how technology might aid their teaching. It suggests that relatively little effort be placed on technologies that are simply substitutions (they are not worth the effort) and that the costs of augmenting technologies be carefully considered (they might not be worth the effort). Note that these suggestions assume that instructors are currently not using technology when, in practice, even novice instructors likely have technological skills like PowerPoint and/or Beamer that might be used for class presentations.[<reflink idref="bib2" id="ref14">2</reflink>] Modification technologies generally show more promise as they enable deeper student understanding, and redefinition technologies can enable entirely new ways of teaching, and they should be carefully considered.</p> <hd id="AN0174338623-4">Teaching constraints: Human limitations and inequalities</hd> <p>Instructors face numerous external constraints. Some that are inherent to the teaching process are described in Chew and Cerbin ([<reflink idref="bib7" id="ref15">7</reflink>]), who list nine challenges, from student mental mindset to insufficient prior knowledge to constraints of selective attention. They argue that quality teaching should address these cognitive challenges, and careful use of technology can assist in this regard. For instance, students often have poor "metacognition" (monitoring their own thinking when learning), and an instructor can use their LMS (like Canvas) to provide exercises like exam wrappers (Eberly Center n.d.) to help students improve this skill. Exam wrappers ask students how they studied for an exam, how they might study better, and what topics they found difficult to encourage them to think metacognitively. The term wrapper comes from these questions being posed on a piece of paper that is wrapped around a paper exam before graded exams are passed back to students. The student fills out the wrapper when reviewing the exam and then hands it back to the instructor. Shortly before the next exam takes place, the instructor hands the filled-out wrappers back to students so they can reflect on their exam preparation methods. In the electronic world, wrappers are done in the LMS, and students are asked to review it before the next exam. Chew and Cerbin ([<reflink idref="bib7" id="ref16">7</reflink>]) also describe how students can come to a course with varied prior knowledge, and this might be assessed at the start of the semester with a quiz in an LMS. Students' misconceptions can be uncovered with Just in Time Teaching (JiTT) assignments (Simkins and Maier [<reflink idref="bib30" id="ref17">30</reflink>]; <emph>Starting Point</emph> n.d.) or pre-class quizzes, which again can be posted in an LMS. Finally, Chew and Cerbin ([<reflink idref="bib7" id="ref18">7</reflink>]) describe students' limited working memory—they can process about four "chunks" of information at one time. A chunk might be a definition or simple concept. To address this constraint, instructors might orient in-class instruction around clicker questions to focus the class on discrete, individual concepts that students can easily process.</p> <p>Further constraints arise from inequalities. Some students might not have access to the technology of their peers, are burdened by poor or nonexistent Wi-Fi at home, or have less capable computers, such as Chromebooks or tablets. Further, institutional inequalities abound; for example, some institutions provide computer grants for students in need. Even within institutions, technology might well vary among classrooms and perhaps among instructors.</p> <p>Instructors also should consider their own limits. One is their working memory—much like students—but what constitutes a chunk likely grows with experience. For example, cost curves from a micro principles course might be one chunk for an experienced economics instructor with a PhD, but perhaps more than four chunks for a principles-level student. This limitation suggests that novice instructors should be careful with the amount of technology they employ in the classroom as they likely have little experience with it (although they likely have considerable experience with noninstructional technologies). That is, for the first semester or two, they might use little more than PowerPoint/Beamer and their LMS as they get used to the other cognitive demands of the classroom, such as course content and questions from students. Further, novice instructors likely have little time to devote to learning new technologies, given the demands on their time outside the classroom. As the years go by, and they gain experience and can chunk more information, they might start to explore additional technologies that their more seasoned peers employ.</p> <hd id="AN0174338623-5">Optimal use of technology</hd> <p>Adopting technology is distinct from using that technology well. Deslauriers, Schelew, and Wieman ([<reflink idref="bib10" id="ref19">10</reflink>]) offer an illuminating example. They compare the learning of one week's material in two similar sections taught by two instructors. Both instructors used clickers, but there was a difference in learning between the two sections of about 2.5 standard deviations. One instructor used clickers in an obvious but less than optimal way (checking understanding after he lectured), while the other instructor used clickers to implement deliberate practice. That is, the clicker questions targeted common misunderstandings in the form of a question. The correct answer was not obvious to most students, while the distractors included common but incorrect student views. Further, Peer Instruction was used to ensure robust discussion of the question, including an explanation from the instructor on how the topic at hand connects to other course topics. An economics question of this type, which I used in macro principles, is, "Say that inflation fell. Then the price level (measured by the CPI or GDP deflator) would be sure to fall as well. A. true B. false." As many students confuse deflation and disinflation, this question directly addresses a misunderstanding. When implemented with Peer Instruction, all the elements of deliberate practice are addressed: attempting a challenging task that takes one's full attention with extensive feedback that connects to things students already know.</p> <p>One excellent guide to optimal clicker instruction is "<emph>Clickers/Personal Response Systems</emph>" (CWSEI n.d.). Note that clickers can be used in a wide variety of contexts, from very large classes to small seminars. As described in Levy, Yardley, and Zeckhauser ([<reflink idref="bib19" id="ref20">19</reflink>]), students will often herd when they raise their hands, and perhaps this occurs with other types of involvement, like discussions. With a clicker, students vote anonymously. In current parlance, they provide a safe method of student feedback. Clickers are a very accessible technology as the monetary costs to students are often zero, and their software can be run on many devices, from phones to tablets to laptops.</p> <p>Many instructors are likely ignoring a valuable resource on their campus that they should search out for the optimal use of technology—their teaching and learning center (most campuses have one). They offer instruction on technologies, such as the institution's LMS. These centers typically offer workshops, seminars, and confidential consultations. They go by various names, and department colleagues will likely know the local variant. Or one might check the list of centers from their professional organization (POD Network [<reflink idref="bib27" id="ref21">27</reflink>]).</p> <hd id="AN0174338623-6">Challenges related to students' technologies</hd> <p>Students can be avid users of technology, although not always in ways that instructors might wish. Most instructors are probably familiar with Web sites such as Chegg and Course Hero (although there are many others), where students share worked homework and exam answers. These sites can be quite responsive—Lancaster and Cotarlan ([<reflink idref="bib18" id="ref22">18</reflink>]) found that answers to online exam questions can appear during exams. Other technologies that aid cheating include sites like Symbolab Math Solver (<emph>Symbolab.com</emph> n.d.) that can solve equations for unknowns, integrate and differentiate functions, and work many types of linear algebra problems. Users can be shown each step of a procedure, (https://<ulink href="http://www.symbolab.com/solver/step-by-step),">www.symbolab.com/solver/step-by-step),</ulink> which can be copied into online exams and homework assignments.</p> <hd id="AN0174338623-7">Chatbots, large language models, and artificial intelligence</hd> <p>In November 2022, the firm OpenAI introduced ChatGPT, a "chatbot" based on their GPT-3.5 and GPT-4.0 software (Schulman et al. [<reflink idref="bib29" id="ref23">29</reflink>]). It uses a large language model, which is trained on a massive amount of human-generated text (books, Web sites, online discussions, etc.) across a wide variety of topics.[<reflink idref="bib3" id="ref24">3</reflink>] As the name suggests, one types questions to the software, and it replies, much like a person would. As this is written some eight months after ChatGPT's introduction, it appears that this technology will have a significant impact on teaching as students can find reasonably good answers to almost any question simply by querying this software. To illustrate, it performed very well on the <emph>Test of Understanding in College Economics</emph> (TUCE) (Walstad and Rebeck [<reflink idref="bib37" id="ref25">37</reflink>]), an assessment used in principles courses. ChatGPT scored at the 91st percentile on the micro portion of the TUCE and the 99th percentile on the macro version (Geerling et al. [<reflink idref="bib14" id="ref26">14</reflink>]). Two headlines in the <emph>Chronicle of Higher Education</emph> in 2023 likely illustrate the concerns of many instructors: "I'm a Student. You Have No Idea How Much We're Using ChatGPT" (Terry [<reflink idref="bib36" id="ref27">36</reflink>]) and "GPT-4 Can Already Pass Freshman Year at Harvard" (Bodnick [<reflink idref="bib4" id="ref28">4</reflink>]). A further concerning headline is "The Homework Apocalypse" (Mollick [<reflink idref="bib24" id="ref29">24</reflink>]); the author, a frequent online commentator on chatbots, is referring to the challenges of assigning homework in this new era. It is not clear how instructors might respond to chatbots. In part, in-class exams and writing might play a more prominent role. For homework assignments, one might grade for completion instead of correctness, as the incentive to use chatbots will be less. Perhaps one might ask higher-order questions in place of calculations, but Bodnick ([<reflink idref="bib4" id="ref30">4</reflink>]) suggests that this might be problematic as the author finds that ChatGPT writes required essays for first-year courses at Harvard quite well.</p> <p>While many students appear to be using chatbots to assist in their courses, instructors can use them as well. Mollick and Mollick ([<reflink idref="bib25" id="ref31">25</reflink>]) offer five suggestions on how instructors can use chatbots: (<reflink idref="bib1" id="ref32">1</reflink>) producing varied examples, (<reflink idref="bib2" id="ref33">2</reflink>) providing multiple explanations, (<reflink idref="bib3" id="ref34">3</reflink>) developing low-stakes tests, (<reflink idref="bib4" id="ref35">4</reflink>) assessing student learning, and (<reflink idref="bib5" id="ref36">5</reflink>) aiding distributed practice. Another possible use is summarizing a mass of student answers (e.g., one-minute papers) to get a sense of students' understanding of a topic.</p> <hd id="AN0174338623-8">Future technologies</hd> <p>In June 2023, Apple introduced a virtual reality headset (Gershgorn [<reflink idref="bib15" id="ref37">15</reflink>]). It does not appear to have many immediate teaching applications, given its price of $3,500 and its bulk—about the size of large ski goggles. However, a possible successor, the so-called "Apple Glasses," might have more impact. One source (Kozuch [<reflink idref="bib17" id="ref38">17</reflink>]) reports they would look similar to regular glasses, but users will see a display much like a cell phone's. Instructors concerned with academic integrity on in-class exams will clearly be challenged, and it is not clear how one might respond.</p> <p>The pandemic introduced many instructors and students to video-conferencing software, most notably Zoom. While it enabled remote synchronous instruction and office hours, many felt its limitations, including "Zoom Fatigue" (Bailenson [<reflink idref="bib2" id="ref39">2</reflink>]). Future video-conferencing software is likely to be more realistic than the small pictures of remote people now seen on screens. Hints of what will be possible are illustrated by Google Starline (Bavor [<reflink idref="bib3" id="ref40">3</reflink>]), where the remote person appears to be sitting across a table from you in 3-D. Or education-specific video-conferencing software might become common, like the "Forum Learning Environment" (Minerva Project n.d.). In the SAMR model, these technologies would likely count as "modification" or "replacement" technologies and thus be worthy of consideration in the years to come.</p> <hd id="AN0174338623-9">Conclusion</hd> <p>In this article, I focus on general principles new instructors should consider when selecting technology for their classes. Specific recommendations are difficult because teaching technology is rapidly changing, and there is great heterogeneity in economists' institutions and students. Thus, this article outlines general principles new instructors should consider:</p> <p></p> <ulist> <item> Technology should, if possible, support deliberate practice, which encompasses a broad array of active learning techniques. Deliberate practice involves asking challenging questions and giving students prompt and complete feedback that connects to other course concepts, facts, and procedures.</item> <p></p> <item> New instructors should select classroom technologies that are very straightforward to use, given that many are teaching new courses and are likely new to teaching. In cognitive science terms, instructors need to be aware of their limited working memory as well as the time they must devote to learning new technologies.</item> <p></p> <item> The SAMR (Substitution, Augmentation, Modification, Redefinition) framework gives instructors a way to categorize technology choices. Some technologies are simply substitutions (think PowerPoint for a blackboard if just presenting text), others redefine teaching, and some are in between these two extremes.</item> <p></p> <item> Finally, instructors should be aware of their own experience and comfort with using technology.</item> </ulist> <hd id="AN0174338623-10">Acknowledgments</hd> <p>The author thanks the symposium and the <emph>Journal</emph> editors for many helpful comments that greatly improved this article.</p> <hd id="AN0174338623-11">Disclosure statement</hd> <p>The author reports there are no competing interests to declare.</p> <ref id="AN0174338623-12"> <title> References </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Allgood, S., G. Hoyt, and K. McGoldrick. 2018. Teacher training for PhD students and new faculty in economics. 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Web site. https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/.</bibtext> </blist> </ref> <ref id="AN0174338623-13"> <title> Footnotes </title> <blist> <bibtext> The seminal paper is Ericsson, Krampe, and Tesch-Römer ([12]). Deliberate practice has been the foundation of several important papers in physics education research, including Deslauriers, Schelew, and Wieman ([10]), Jones, Madison, and Wieman ([16]), and McCarty and Deslauriers ([20]), while in economics there is Boyle and Goffe ([5]).</bibtext> </blist> <blist> <bibtext> Those wishing to improve their slides for maximum student understanding should follow Davis ([9]).</bibtext> </blist> <blist> <bibtext> Two descriptions of large language models are Newport ([26]) and Wolfram ([39]).</bibtext> </blist> </ref> <aug> <p>By William L. Goffe</p> <p>Reported by Author</p> </aug> <nolink nlid="nl1" bibid="bib23" firstref="ref2"></nolink> <nolink nlid="nl2" bibid="bib13" firstref="ref4"></nolink> <nolink nlid="nl3" bibid="bib33" firstref="ref5"></nolink> <nolink nlid="nl4" bibid="bib21" firstref="ref6"></nolink> <nolink nlid="nl5" bibid="bib28" firstref="ref7"></nolink> <nolink nlid="nl6" bibid="bib38" firstref="ref9"></nolink> <nolink nlid="nl7" bibid="bib31" firstref="ref10"></nolink> <nolink nlid="nl8" bibid="bib19" firstref="ref11"></nolink> <nolink nlid="nl9" bibid="bib32" firstref="ref13"></nolink> <nolink nlid="nl10" bibid="bib30" firstref="ref17"></nolink> <nolink nlid="nl11" bibid="bib10" firstref="ref19"></nolink> <nolink nlid="nl12" bibid="bib27" firstref="ref21"></nolink> <nolink nlid="nl13" bibid="bib18" firstref="ref22"></nolink> <nolink nlid="nl14" bibid="bib29" firstref="ref23"></nolink> <nolink nlid="nl15" bibid="bib37" firstref="ref25"></nolink> <nolink nlid="nl16" bibid="bib14" firstref="ref26"></nolink> <nolink nlid="nl17" bibid="bib36" firstref="ref27"></nolink> <nolink nlid="nl18" bibid="bib24" firstref="ref29"></nolink> <nolink nlid="nl19" bibid="bib25" firstref="ref31"></nolink> <nolink nlid="nl20" bibid="bib15" firstref="ref37"></nolink> <nolink nlid="nl21" bibid="bib17" firstref="ref38"></nolink> |
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| Items | – Name: Title Label: Title Group: Ti Data: Educational Technology for Teaching Economics - Where to Start and How to Grow? – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22William+L%2E+Goffe%22">William L. Goffe</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Journal+of+Economic+Education%22"><i>Journal of Economic Education</i></searchLink>. 2024 55(1):77-84. – Name: Avail Label: Availability Group: Avail Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 8 – Name: DatePubCY Label: Publication Date Group: Date Data: 2024 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Descriptive – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Beginning+Teachers%22">Beginning Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Economics+Education%22">Economics Education</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Technological+Literacy%22">Technological Literacy</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1080/00220485.2023.2274026 – Name: ISSN Label: ISSN Group: ISSN Data: 0022-0485<br />2152-4068 – Name: Abstract Label: Abstract Group: Ab Data: New economics instructors face numerous challenges when selecting technology for their courses. Because economists teach at a variety of institutions with diverse student bodies and since technology continues to evolve, this article focuses on general principles that novice instructors should consider when selecting technology for their courses. One principle is that technology should support "deliberate practice," which encompasses many types of active learning. Instructors should be aware of the various constraints they face, including the numerous cognitive challenges to effective teaching, limitations to their own "working memory," and potentially limited resources of their students and institutions. The "Substitution, Augmentation, Modification, Redefinition" (SAMR) framework is introduced to explain how technology might influence instruction. Finally, instructors should learn how to optimally use the technology they select. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2024 – Name: AN Label: Accession Number Group: ID Data: EJ1406468 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/00220485.2023.2274026 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 77 Subjects: – SubjectFull: Beginning Teachers Type: general – SubjectFull: Economics Education Type: general – SubjectFull: Educational Technology Type: general – SubjectFull: Technological Literacy Type: general Titles: – TitleFull: Educational Technology for Teaching Economics - Where to Start and How to Grow? Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: William L. Goffe IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 0022-0485 – Type: issn-electronic Value: 2152-4068 Numbering: – Type: volume Value: 55 – Type: issue Value: 1 Titles: – TitleFull: Journal of Economic Education Type: main |
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