The sudden move to remote online instruction, coupled with social justice issues plaguing the United States, has forced college and university instructors to grapple with what it means to be a good teacher in socially distanced, unpredictable, and emotionally charged circumstances.

As instructional designers, we have noticed an undercurrent in our interactions with new and experienced university instructors that indicates they are doubting their teaching skills, confronting uncomfortable questions about their roles, making pedagogical decisions on the fly, and trying to use technologies that were once only written into science fiction novels.

While the move to remote teaching has been challenging, it has also provided an opportunity to reenvision pedagogy. As colleges and universities have collectively moved online, teaching and learning professionals can leverage mobile learning (m-learning) to inform and facilitate effective teaching in a virtual environment.

Contemporary m-learning definitions and discourse focus on using technologies that support the mobility of learners and teachers and that are based on constructivist and learner-centered pedagogies that promote individualization, flexibility, and communal engagement with content regardless of whether a course is online or face-to-face. To benefit from affordances like these, Yu (Aimee) Zhang, CEO of WEMOSOFT in Wollongong, Australia, recommends using m-learning in formal higher education to supplement face-to-face or online classes.^Footnote2 Near-ubiquitous mobile-device ownership and a stable combination of agile technological infrastructure and widespread internet connectivity offer opportunities for the key affordances and strategies of m-learning to take center stage during the coronavirus pandemic.^Footnote3 That is not to say that all students (or instructors) have fully equitable opportunities to access tertiary education through mobile devices—as the pandemic has revealed—but it does emphasize the current collective ability among colleges and universities to maintain a somewhat reasonable level of instructional continuity—something that would not have been possible just ten years ago.^Footnote4

Amid the challenges of emergency remote teaching and learning, college and university instructors confront a complex set of pedagogical decisions as they try to balance the affordances and constraints of technologies with student access, learning outcomes, and the instructor’s teaching goals.

Our Mobile Learning Special Interest Research Group has been investigating this pedagogical balancing act for a few years, and although our participants were teaching face-to-face classes before the pandemic, our findings about the ability of instructors to achieve their teaching goals via m-learning remain applicable—and possibly more relevant—today.^Footnote5

Teaching Goals: Prevalent Themes

As instructional designers, part of our work focuses on supporting instructors as they integrate technologies to improve their teaching. Understanding instructors’ experiences provides invaluable insight into the benefits of m-learning. This article presents findings from interviews with nineteen instructors (at four University of California [UC] campuses) who were using m-learning strategies in their teaching before the pandemic.

We examined the instructors’ perceptions of how m-learning supported or helped them to achieve their teaching goals. During the interviews, instructors told us that integrating m-learning in their courses supported their teaching goals by increasing student engagement, allowing students to learn specific skills, enabling the creation and use of analytics in class, and boosting instructor efficiency.

Student Engagement

The instructors noted that the use of m-learning helped to increase student engagement by stimulating their interest, creating a safe environment, building a class community, and providing multiple opportunities for and means of participation.

First, the instructors we interviewed for our study said that they used mobile strategies in ways they felt would stimulate student interest and motivation. For example, Ozcan Gulacar, a member of the chemistry faculty at UC Davis, found that student engagement occurred by heightening students’ ownership of their learning.

Giving students a chance to share their answers via proper technology increases their ownership of the material, and they become more engaged in discussions. They pay more attention to the explanations. Basically, their interest in learning the right answer increases immensely.^Footnote7

Similarly, our interviews showed the importance of student ownership when they were collecting and generating data as part of their learning experiences; students’ agency in that process kept them motivated and engaged (see “Analytics for and about Learning” below).

Second, instructors felt that using m-learning increased student engagement by creating a safe environment in the course. Interestingly, this safe environment was created in one of two opposing ways: Some students appreciated that mobile devices lowered communication barriers so they could get to know their peers better, while other students liked that using personal-response systems allowed them to participate anonymously in discussions, thus encouraging their engagement.

As Heather Macias, now an education faculty member at California State University, Long Beach, explained, “The anonymity and low stakes make [students] more willing to [share their ideas] because nobody knows what” any individual student responded.^Footnote8

Third, m-learning allowed instructors to create a sense of community because the familiarity bred through the use of m-learning strategies helped to make large classrooms feel smaller. Emma Levine, now a member of the music faculty at California Polytechnic State University, reported that when her class uses Slack for instant messaging, “[students] don’t feel anonymous. They come to [class] because I know who they are, and other people know who they are. Having that sense of belonging, wanting to come, and [having] some type of accountability” encourages them to attend.^Footnote9

Finally, students could engage more often during the course, as they had multiple opportunities and means to participate. As Macias said, “[Using mobile technology] gives me more . . . ways to get students hooked into a lesson or participate. I like it because it gives all the students the chance to participate, assuming they all have . . . access to a device, without the pressure of [having] to raise [their] hand.”^Footnote10

When their teaching goals centered around increasing student engagement, instructors appeared to feel that mobile technologies helped to stimulate student interest and motivation, create a safe environment and a sense of community, and provide students with multiple opportunities and ways to participate. It is interesting to note that these four benefits of m-learning occurred in overlapping and intersecting ways, not in isolation.

Specific Skills and Concepts

Instructor comments indicated that m-learning facilitated improved student mastery of specific skills and concepts in two important ways. First, instructors felt that m-learning helped them to teach students specific digital skill sets that they needed for their future careers. Nic Barth, a member of the geology faculty at UC Riverside, said that m-learning skills help to provide students with a competitive advantage:

The motivation [for using iPads] was to not use [them] as a replacement for teaching students how to map with pencil and paper but to extend it to the next skill level, where okay now you know how to do that, now we can train you how to do this digitally. And that’s something that is a highly sought-after, marketable skill that they can then take and make themselves more competitive either in grad school or in the job pool.^Footnote11

Second, instructors indicated that integrating mobile learning allowed them to more easily create rich learning environments in which to teach complex concepts. For example, Ashish Sood, a business faculty member at UC Riverside, uses a fully online, game-based approach to teach his students about empathy in a business setting. He describes how students learn about risk tolerance by completing a pricing strategy simulation:

In a standard case analysis, you [try to] put yourself in the shoes of a company or a manager and [consider why a manager chose a particular strategy]. But when you are actually playing a simulation game . . . it changes the perspective to, “How should I decide? What is the best way to think about this issue?” and that’s when the learning and the understanding of the concept really sinks in.^Footnote12

Whether making use of simulations, visual representations, or demonstrations, instructors who used mobile technologies to illustrate or expand concepts in a more concrete way found that students could more easily understand and apply those concepts, skills, and methods. Often, the application of the technology was taught for future professional careers, and skills or concepts were made relevant by providing opportunities to apply twenty-first-century digital skills to authentic, real-world problems or contexts.

Analytics for and about Learning

Instructors noted that m-learning gave students the opportunity to practice collecting and analyzing data, contribute data to course content, and demonstrate understanding in formative assessments.

Randall Long, who is currently a postdoctoral research associate at the Holden Arboretum in Kirtland, Ohio, wanted to provide more robust opportunities for his students to fully develop sampling methods and data-analysis skills. His teaching goal was to have students create a large dataset from their fieldwork to complete their final group paper.

Long asked students to play Pokémon Go and systematically collect Pokémon data in a Google Sheet over a few weeks. After students used Pokémon Go to practice sampling concepts and methods, Long was impressed by the obvious improvement in the substance and overall quality of the group papers compared to those from previous years.^Footnote13

Student-generated data can also help to facilitate meaningful class discussions. Bob Blake, a professor in the Department of Spanish and Portuguese at UC Davis, noted that using mobile technologies in his linguistics class helped to fuel discussions about course content because students themselves were represented in the data. He said that he uses mobile technology to get students to talk and share with each other.

Nobody wants to talk or share very much about their language. It’s a very personal thing. . . . So, we try to use technology to kind of give us a screen to look through. . . . They’ll type in [a word or phrase from their language in response to a scenario], and then suddenly I have all of that data right there. . . . So, we just analyze it, and it provides me the raw data for the types of points I’m trying to make [about language use].^Footnote14

These student-generated examples became the data that was used to teach course content. Drawing from real-life examples prompted meaningful discussions.

Finally, data collected from students in formative assessments provided an invaluable opportunity for some instructors to gauge student understanding. Shane Jimerson, a professor in the Gevirtz Graduate School of Education at UC Santa Barbara, described how he uses data collection to gauge student comprehension in real time:

During the class, I tend to use [Kahoot] as a way of seeing what folks are knowledgeable of, and then that informs me in the moment that “we already know about this,” based on the readings and discussions and other resources. But then there seems to be a few [questions] where there is more variation in the responses. So then I can provide further discussion and exploration to try to make that clear.^Footnote15

In Jimerson’s case, using Kahoot to formatively assess students’ learning provided an opportunity in which he could immediately address any confusion students were having or move on to more difficult concepts.

These examples highlight how instructors leveraged m-learning strategies—in which students collected or generated data—for teaching and learning. These techniques invited students to be active participants and make important contributions to the exchange of ideas. Additionally, real-time learning analytics for formative assessment immediately informed instructors about students’ knowledge gaps.

Efficiency

Instructors also noted that m-learning allowed them to get through content more quickly or deeply and improve the speed of the feedback cycle.

Barth distributed “geo pads,” iPads equipped with GIS software, to teach skills and concepts needed for field mapping. He said that this integration of mobile technology resulted in “surprise” time-saving affordances, allowing students time to dig into the more meaningful aspects of the content.

[The use of iPads] simplifies and makes a lot of things more efficient, such [as] the more mundane task [of] locating yourself on a map, for example. It could take a minute, but if you have a tablet that has built-in GPS, it’s a second. Or, if you’re taking a measurement with the tablet, that’s like two or three seconds versus like a minute of playing around with the compass to take that same measurement. And so it’s making things a lot more efficient. [Students] can then focus more of that time on actually understanding what’s going on around them using more critical-thinking skills.^Footnote16

Jim Burnette, an academic coordinator at UC Riverside, noted that using e-notebooks made the feedback cycle more efficient:

The paper notebooks took a little while to grade, and so the feedback cycle was a little too slow. So [students] didn’t improve very much in their notebook skills. I think having gone to the e-notebook made the feedback cycle much faster; [students] are actually keeping better notebooks.^Footnote17

In these cases, mobile technologies made teaching more efficient and provided students the opportunity to spend more time digging into the more meaningful aspects of the course content. In addition, mobile technologies also provided the instructor the opportunity to give students feedback more quickly, resulting in improvements in students’ work.

Takeaways

While the use cases in this study are all unique, span disciplines, and largely represent m-learning within face-to-face courses, m-learning strategies could also help to guide instructors’ pedagogical balancing act during emergency remote teaching and beyond. This study demonstrates the variety of ways that m-learning technologies can help instructors in their ongoing efforts to become better teachers:

• Build and maintain classroom community by creating safe spaces that allow for peer interaction as well as anonymity.
• Increase student interest and motivation by providing multiple means and opportunities for participation.
• Illustrate concepts or topics more clearly.
• Develop students’ emotional, cognitive, and technology-based skills for their future careers.
• Increase engagement by having students use their mobile devices to generate, collect, and analyze data.
• Identify and adapt to gaps in student learning.
• Facilitate a more efficient feedback cycle for student learning.
• Get through basic concepts more quickly, allowing students more time to engage deeply with complex concepts.

Although our study focused on faculty members’ experiences, research on student perspectives demonstrates that m-learning benefits students in similar ways (by creating safe spaces for peer interaction, increasing student interest by offering multiple opportunities to participate, and supporting students who increasingly rely on mobile technology).^Footnote18

As instructors and instructional designers, it is essential that we understand the innovative ways in which using m-learning helps us to achieve our teaching goals during this time of instructional upheaval. As a majority of students use mobile devices to complete online coursework, and almost all students have more than one mobile device, designing with m-learning in mind is essential to support student learning, provide more equitable access, and improve instructors’ confidence in their ability to grapple with pedagogical issues in new ways.^Footnote19

By: Mindy Colin, Samantha Eastman, Margaret Merrill and Alex Rockey

Source: Leveraging Mobile Technology to Achieve Teaching Goals | EDUCAUSE

Notes

1. “Mobile Learning,” EDUCAUSE (website), n.d., accessed January 19, 2021. Jump back to footnote 1 in the text.↩
2. Yu (Aimee) Zhang, “Characteristics of Mobile Teaching and Learning,” in Handbook of Mobile Teaching and Learning, eds. Yu (Aimee) Zhang and Dean Cristol (Berlin, Heidelberg: Springer, 2019), 1–21. Jump back to footnote 2 in the text.↩
3. Michael M. Grant, “Difficulties in Defining Mobile Learning: Analysis, Design Characteristics, and Implications,” Educational Technology Research and Development 67 no. 2 (January 2019): 361–388. Jump back to footnote 3 in the text.↩
4. Nate Ralph, “Perspectives: COVID-19, and the Future of Higher Education,” Bay View Analytics (website), 2020. Jump back to footnote 4 in the text.↩
5. Alex Rockey, et al., “Spotlighting Innovative Use Cases of Mobile Learning,” The Emerging Learning Design Journal 6 no. 1 (2019); Mindy Colin, et al., “M-Learning at UC: Practices, Affordances, and Teaching Styles,” (poster presented at ELI Annual Meeting, Anaheim, CA, February 19, 2019). Jump back to footnote 5 in the text.↩
6. N refers to number of participants. Jump back to footnote 6 in the text.↩
7. Ozcan Gulacar, interview by authors, audio recording, Davis, November 20, 2017. Jump back to footnote 7 in the text.↩
8. Heather Macias, interview by authors, audio recording, Santa Barbara, February 16, 2018. Jump back to footnote 8 in the text.↩
9. Emma Levine, interview by authors, audio recording, Santa Barbara, February 2, 2018. Jump back to footnote 9 in the text.↩
10. Macias, interview, February 16, 2018. Jump back to footnote 10 in the text.↩
11. Nic Barth, interview by authors, video recording, Riverside, December 14, 2017. Jump back to footnote 11 in the text.↩
12. Ashish Sood, interview by authors, video recording, Riverside, March 16, 2018. Jump back to footnote 12 in the text.↩
13. Randall Long, interviews by authors, Santa Barbara, February 16, 2018; October 26, 2018. Jump back to footnote 13 in the text.↩
14. Bob Blake, interview by authors, audio recording, Davis, November 30, 2017. Jump back to footnote 14 in the text.↩
15. Shane Jimerson, interview by authors, audio recording, December 1, 2017. Jump back to footnote 15 in the text.↩
16. Nic Barth, interview by authors, video recording, Riverside, December 14, 2017. Jump back to footnote 16 in the text.↩
17. Jim Burnette, interview by authors, video recording, Riverside, February 13, 2018. Jump back to footnote 17 in the text.↩
18. See, for example: Enrique Alvarez Vazquez, Manoel Cortes-Mendez, Ryan Striker, Lauren Singelmann, et al., “Lessons Learned Using Slack in Engineering Education: An Innovation-Based Learning Approach,” (presentation, 2020 ASEE Virtual Annual Conference, Virtual Online, June 22, 2020); Jorge Fonseca Cacho, “Using Discord to Improve Student Communication, Engagement, and Performance,” (poster presentation, UNLV Best Teaching Practices Expo, University of Nevada Las Vegas, January 23, 2020). Jump back to footnote 18 in the text.↩
19. David L. Clinefelter, Carol B. Aslanian, Andrew J. Magda, Online College Students 2019: Comprehensive Data on Demands and Preferences, research report, (Louisville, KY: Wiley edu, LLC, June 2019); “Mobile Fact Sheet,” PEW Research Center, Internet & Technology, June 12, 2019. Jump back to footnote 19 in the text.↩

Mindy Colin is an Instructional Consultant at UC Santa Barbara.

Samantha Eastman is an Instructional Design Consultant at UC Riverside.

Margaret Merrill is a Senior Instructional Design Consultant at UC Davis.

Alex Rockey is an Instructional Technologist Instructor at Bakersfield College.

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