Synchronous vs. Asynchronous Classes: Best Practices and Future Trends

Synchronous vs. Asynchronous Classes: Best Practices and Future Trends
Imed Bouchrika, Phd by Imed Bouchrika, Phd
Chief Data Scientist & Head of Content

What is synchronous learning? Synchronous learning occurs when a group of students is engaged in learning at the same time through synchronous learning environments in online education, usually with a teacher or teachers/faculty teaching and facilitating the lessons in real-time.

On the other hand, what is asynchronous learning? Asynchronous learning occurs when a group of students is not learning at the same time in online education. The teacher or teachers/faculty are not teaching and facilitating the lessons in real-time, but rather offline or online through recorded videos. They can also be fully paper-based as long as there is asynchrony in teaching and learning schedules.

Synchronous and asynchronous learning and teaching via video conferencing and online tools have become the de facto curriculum delivery methods in most high schools and universities during the COVID-19 pandemic. Indeed, there is no other practical way to teach and learn the curricula without utilizing online platforms.

This article will discuss the similarities and differences between synchronous vs. asynchronous classes, their pros and cons, some meta-studies on student learning and assessment, student learning styles, course design, hardware and software factors, software functionalities, best practices, and the future of online education in general, with a view toward technological and pedagogical advancements. These are very timely as these 2022 data on higher learning and corporate training indicate.

Synchronous vs. Asynchronous Classes Table of Contents

  1. Pros and Cons of Synchronous vs. Asynchronous Classes
  2. Research Studies (Meta-studies) on Learning Effectiveness
  3. Synchronous and Asynchronous Learning Best Practices
  4. Technology Factors
  5. Student Learning Styles
  6. Trends in Teaching and Learning in the Future “Classroom”

Pros and Cons of Synchronous vs. Asynchronous Classes

Synchronous vs. asynchronous learning each has its pros and cons. Some of these pros and cons for both teacher and learner are as follows.

Synchronous learning


  • Fixed schedules allow for better time management
  • Good for people with fixed work schedules
  • Immediate feedback from professors or teaching assistants
  • Class participation in real-time
  • Good for people who prefer active learning styles
  • Real-time feedback
  • Learning environment like a real classroom
  • Ideal for basic cognitive domain learning (Bloom’s taxonomy)
  • More student-student interaction
  • More student-teacher interaction
  • Live customer support for technical issues


  • For large class sizes, difficulty in expressing one’s ideas
  • More technology requirements (webcam, mike, computer, tablet, mobile device, good and stable ISP, etc.)
  • Fixed schedule limits flexibility
  • Course pace is set by the professor/teacher
  • More challenging for persons with disabilities
  • A quiet place is absolutely necessary
  • Fixed or less time spent with the material

Asynchronous Learning


  • Class activities and assessments have flexible submission dates
  • Good for people with irregular work schedules
  • Good for reflective learning styles
  • Minimal Internet requirements (web browsing and form submission are enough)
  • Course pace is set by the student
  • More time spent with the material
  • Learning environment like a personalized classroom
  • Ideal for higher cognitive domain learning (Bloom’s taxonomy)
  • More time to think
  • More time to research responses
  • Non-live customer support (for technical issues)


  • Time-consuming grading (teachers)
  • Feedback is not in real-time
  • Not for students who procrastinate
  • Lack of interaction with other students
  • Does not cater well to active learning styles
  • Easy to get demotivated
  • Easy to get distracted
  • Impersonal or generic feedback on work submitted
  • Less student-student interaction
  • Less student-teacher interaction

Source: Vielma and Brey, 2021

Research Studies (Meta-studies) on Learning Effectiveness

Student Performance

See, et al’s review found no evidence that learner response systems enhance children’s academic attainment, including technologies that embed gaming features. However, they did find studies that showed that math and reading can be improved using digital formative assessments (See, et al, 2021). More causal research is needed in this area as newer generations of children have grown up being more digitally proficient than previous generations as technology has improved.

Ohio state data (2009–2010 to 2012–2013) on 7 million students in K–12 schools delivering online education, with no brick-and-mortar schools, and have full-time students showed that low-income, lower-achieving white students were more likely to choose e-schools, while minority students from the same classification were more likely to choose traditional charter schools. Very telling is that students in e-schools have worse performance in standardized assessments than those in traditional charter and traditional public schools  (Ahn and  McEachin, 2017).

Of course, there are many other factors that could have affected this result, indicating the need for more research, especially to correct confounding variables.

Teacher Formative Assessments

A meta-review of 52 studies found two main factor categories influencing teachers’ intentions to conduct formative assessment – personal factors (instrumental attitude, self-efficacy, and education and training) and contextual factors (internal school support, external policy, school environment, and cultural norm) (Yan, et al, 2020). This indicates more than just teacher ability and motivation as important factors in student performance assessments; a tightly-integrated support system is implied as a crucial factor.

A review of 55 eligible studies from 11 major databases showed evidence that formative assessments delivered digitally facilitate mathematics and reading learning for young children; however, its effectiveness in other subjects, for older children, or over formative assessment without technology was not demonstrated (See, et al, 2021).

Synchronous and Asynchronous Learning Best Practices

Course Design

A good and well-thought-out course design is essential, especially in online learning. Courses should be highly-structured, especially introductory courses. The course activities, assessments, and technology requirements should all be explicitly written and scheduled, while also allowing for accessibility for students with disabilities. They should also be aligned with the learning outcomes and module learning objectives, so planning a course out takes a lot of thought and time.

Courses can also be blended with synchronous parts like live videos of demos and problem-solving tasks and with asynchronous parts like homework and extra exercises that can be done offline or outside of class hours.

Additionally, the shift from traditional academic learning to competencies-based learning has made online programs more focused and with better alignment of learning objectives with class activities and assessments. Outcome-based Education (OBE) (Spady, 1993) has transformed education to become more standardized, clearer, and more practical. This clearly indicates the synergistic effects of the educational platform with the curriculum it delivers.

Incorporating Bloom’s Taxonomy

Bloom’s taxonomy, revised in 2001, is an excellent guide to planning student learning and learning outcomes. The modern taxonomy has four cognitive domains: factual knowledge, conceptual knowledge, procedural knowledge, and metacognitive knowledge (Armstrong, 2010) that students acquire and develop towards mastery of a subject.

Synchronous classes are ideal for basic cognitive domain learning of factual knowledge and conceptual knowledge, while asynchronous classes are ideal for higher cognitive domain learning of procedural knowledge and metacognitive knowledge.

Of course, combining synchronous and asynchronous modes of instruction and learning can cater to these four domains of knowledge.

Active Learning Strategies

Active learning strategies help lessen passive listening and non-participation and encourage student participation in hands-on activities, student-student interaction, and student-teacher interaction. In addition, students become more engaged with the course material. These strategies are mostly developed and implemented on software platforms by default.

Best Practices—Assessment Presence

In asynchronous online discussions, a factor called Assessment Presence consists of using explicit and measurable performance expectations, criteria, and quality standards, grading student work with constructive feedback and recommendations. The assessment rubrics are expectations, rules, protocols, and scoring and ranking criteria (Wang, 2015), effective for graduate Cybersecurity Technology classes the author taught.

Assessment Presence was found to positively affect student learning and the elements of Cognitive Presence (the extent of constructing meaning through sustained communication), Social Presence (ability to project their personal characteristics into the community), and Teaching Presence (designing educational experience and facilitation) (Wang, 2015).

Best Practices—Constrained Online Nexus of Control

It has been found that problems result from human behaviors and their interactions with system features. In a study of 3,630 students from 2004 to 2012, it was found that video conferencing and immersive virtual environments need to have a nexus of control of software and classroom management to avoid repeat conflicts and limited interaction opportunities. (Warden et al, 2013).

Best Practices—Blended Learning

One recommendation has been to combine synchronous with asynchronous approaches (Moorhouse and Kohnke, 2022). Other recommendations include the use of breakout rooms for smaller and more focused discussion groups,  the use of polling functions for questions and monitoring student understanding,  and allotting time before or after lessons for informal conversations (Moorhouse and Kohnke, 2022).

Source: Tahir, et al, 2022

Technology Factors

Technology—Software Functionalities

In synchronous learning, some effective teaching and learning methods have already been incorporated as modules or functions in modern software and online platforms, including open-source platforms. They can also be used for asynchronous teaching and learning, differing only in their being non-real-time.

These include the following (though not all are present in each particular software package or platform):

  • AI chatbots
  • Automated class attendance monitoring
  • Automated quiz grading in real-time
  • Breakout rooms
  • Chat areas
  • Class recording function
  • Collaborative documents
  • File sharing
  • Gamified course content
  • Graphing functions for real-time class polls on answers/ opinions
  • Interactive discussion boards
  • Lab report experiment data forms
  • Live customer support
  • Live Q and A with teaching assistant/s
  • Live streaming and YouTube integration
  • Live technology boards for technical troubleshooting
  • Polls/ polling function
  • Private message areas
  • Whiteboard with annotation



It is also best to assess what hardware online classes would require. Obviously, synchronous classes require much more hardware, typically, a PC or laptop, microphone, headphones/ earphones, tablet, mobile device, etc. For asynchronous classes, it is typically enough to have a web browser that can fill up forms for the submission of documents or other files. There are no voice or video requirements, usually.

Technology—Internet Connectivity

Internet connectivity is required for both synchronous and asynchronous modes of learning, and high-speed fiber optics connections are increasingly being used in many households and school settings. A 2019 report showed that 70% of households in China have fiber connections, with the United States having the second-worst coverage at 30%; Sweden has 90%, and Lithuania and Latvia both have 100 % fiber coverage (Council on Foreign Relations, 2022). Nowadays, online platforms are ubiquitous and technology is not a big issue in most developed countries, but not for developing countries.

Source: Council on Foreign Relations (2022).

Student Learning Styles

Student learning styles have been studied and characterized using several models, and it is of great importance that these learning styles are incorporated into the course and learning platform development. Teachers need to develop specific pedagogical strategies, which are more personalized and student-centered.

The five families of learning styles are as follows (Coffield, et al, 2004):

Learning styles and preferences:

  1. Are largely constitutionally based, including the four modalities:  Visual, auditory, kinesthetic, tactile (VAKT) (Example: Dunn and Dunn model)
  2. Reflect deep-seated features of the cognitive structure, including ‘patterns of ability’ (Example: Riding model)
  3. Are one component of a relatively stable personality type (Example: Apter model)
  4. Are flexibly stable learning preferences (Example: Allinson and Hayes model)
  5. [Move on from learning styles to ] learning approaches, strategies, orientations and conceptions of learning (Example: Entwistle model)

The most commonly used model is the VAKT modalities model, used in about 70% of studies reviewed for integrating learning styles into adaptive e-learning systems (Truong, 2015).  For the VAKT modalities, the visual and auditory components can easily be incorporated into course design, but the kinesthetic and tactile components do not always lend themselves to the online environment but may be actualized by offline and asynchronous activities, as in lab experiments one can do remotely from home or any location.

Matching and designing courses for different student learning styles would ensure a successful teaching and learning experience. It also allows for tailored and specific pedagogical techniques for special students and would be amenable to AI-assisted teaching in the future.


Self-direction is the ability to have initiative and to organize oneself and is a key ingredient to online learning success. Encouraging self-direction in students is a proven way to help them, especially students who procrastinate a lot and those who are not well-versed in self-directed learning. It has been found that student performance declines because they need a teacher who is physically present to continuously drive their attention to the subject matter (Bork and Rucks-Ahidiana, 2013).

Source: Abouzeid, et al, 2021

Trends in Teaching and Learning in the Future “Classroom”

MOOCs (Massive Open Online Courses)

MOOCs, or massive open online courses, started off as mostly free web-based distance learning programs designed for large numbers of students in various geographical regions and time zones. Typically, the courses are available over the internet free of charge to a large number of people; requests for certificates of course completion may carry fees, and several companies have commercialized the concept and charge for their courses.

Mostly asynchronous, this relatively-new model of education has taken the world by storm, offering such courses as machine learning and data science, engineering, .mathematics, life sciences, pharmaceutical sciences, and many more technical subjects. They are typically taught by professors who are subject matter experts in their respective fields, lending credibility and legitimacy to the course taken. Perhaps the most famous classes that inspired MOOCs (Pappano, 2012) were those on artificial intelligence and machine learning, started by Dr. Andrew Ng of Stanford University, now on YouTube.

Typically, classes are conducted by watching recorded video lectures, reading the assigned material (often provided as PDF handouts and books), doing the problems and exercises, taking online quizzes and exams, and participating in discussion forums with other online students.

Virtual Reality (VR) and Augmented Reality  (AR) Classrooms

Virtual reality (VR), coined in 1987 by Jaron Lanier, is “the use of computer modeling and simulation that enables a person to interact with an artificial three-dimensional (3-D) visual or other sensory environment” (Lowood, 2021). Computer-generated virtual environments are experienced immersive with the use of goggles, headsets, gloves, and/ or body suits. This has been used in many diverse education areas, including anatomy, art, biology, chemistry, engineering, geography, hospital training, music, physics, space science and sports science, among many others (Virtual Human Interaction Lab, Stanford University, 2022).

This technology can be used in both synchronous and asynchronous learning. For example, virtual anatomy and surgery courses can explore a simulated operation of a virtual patient. In an orthopedic knee surgery study from Johns Hopkins University in the Journal of the American Academy of Orthopaedic Surgeons, it was found that “Training with VR was subjectively rated higher in value compared with reading/video methods and had similar performance outcomes compared with training with PS” [physical simulation] (Margalit, et al, 2022).

Synchronous classes enable the participants to ask questions and confirm surgical steps with the professor in real-time and avoid costly and even fatal mistakes. The learning is highly immersive, personal, and very practical, allowing students to learn firsthand very efficiently. Asynchronous classes can be utilized for a more personal practice time, essential for performing surgeries for the first few times. Practicing surgical steps can make the work go more smoothly and efficiently.

A related technology is augmented reality (AR), where digital objects are added to a live scene to enhance learning. Examples of AR include enhanced navigation systems for driving and geography with superimposed routes over the live view of the road, sports diagrams over a live game broadcast, furniture and housewares interior design simulators, military fighter pilots’ flight data displayed in their helmet visors, neurosurgeries with a 3-D brain projection to aid in surgeries, views of ancient civilizations over today’s ruins at historical sites like Pompeii in Italy, and many more (The Franklin Institute, 2022). These can be utilized in both synchronous and asynchronous modes of learning.

Synchronous vs. Asynchronous Classes—Future Market Segmentation

Continuing education is not just for high school, college students, or graduate students. There are also many potential students who are different types of learners. These types include, but are not limited to, the following:

  • Corporate skills learners are those whose companies require them to acquire and develop new skills to enhance their work.
  • Industry certification learners are those who need technical skills and knowledge in their specific industry; very common among software and hardware engineers
  • Hobbyist learners learn new skills to gain new hobbies or to improve their current craft.
  • Upgraders are learners who need to upgrade highly-technical skills like learning a programming language deeper, or learning how to code more complex applications.
  • Life-long learners are typically accomplished professionals who would like to learn new things.
  • Reviewer learners are those who need to brush up on topics in their general education programs for upcoming teaching jobs.
  • Licensure learners are those preparing for board exams or licensure tests. And the list goes on.

Source: Gallup Poll - The State of Higher Education 2022 Report (2022), (n= 3,002)

Synchronous vs. asynchronous classes do not need to be mutually exclusive. Well-designed programs can incorporate both components into a curriculum and provide a wide variety of options for different personalities, learning styles, and schedules.

More Online Synchronous and Asynchronous Degree Programs Needed

In the U.S.,  the 2022 Gallup Poll’s  State of Higher Education Report found that among U.S. adults without a college degree, who are not currently enrolled in any certificate or college degree program, 44% considered enrolling in a bachelor’s degree, associate degree, industry certification, or certificate program in the past two years, and 85% of those recently enrolled in a certificate or degree program, but stopped during the COVID-19 pandemic, have considered re-enrolling (Gallup, 2022).

Current trends in higher education include attempts to increase the affordability of college tuition via online education, shifting campus demographics, nontraditional students, competency-based education, and college closures and mergers, among others. These are all our present realities and signal the need for more online synchronous and asynchronous programs to meet the demands of individual learning styles and the modern workplace.



  • Abouzeid, E., Fouad, S., Wasfy, N. F., Alkhadragy, R., Hefny, M., Kamal, D. (2021). Influence of Personality Traits and Learning Styles on Undergraduate Medical Students’ Academic Achievement. Advances in medical education and practice, 12, 769–777. DOI:
  • Ahn, J., McEachin, A. (2017). Student Enrollment Patterns and Achievement in Ohio’s Online Charter Schools. Educational Researcher, 46(1), 44–57. DOI:
  • Armstrong, P. (2010). Bloom’s Taxonomy. Vanderbilt University Center for Teaching. Retrieved July 19, 2022 from
  • Bork, R., & Rucks-Ahidiana, Z. (2013, October). Role ambiguity in online courses: An analysis of student and instructor expectations (Working Paper No. 64). Retrieved July 18, 2022 from the Community College Research Center website:
  • Coffield, F., Moseley, D., Hall, E., Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning: a systematic and critical review. Learning & Skills Research Centre, London. Retrieved July 18, 2022 from:
  • Council on Foreign Relations (2022). Open Access Fiber to Improve U.S. Internet Connectivity. Retrieved July 19, 2022 from
  • Gallup, Inc. (2020). 2019 Graduate Outcomes Benchmark Report. Retrieved July 19 from:
  • Lowood, H. E. (2021). Virtual Reality. Encyclopedia Britannica. Retrieved July 20, 2022 from:
  • Margalit, A., Suresh, K. V., Marrache, M., Lentz, J. M., Lee, R., Tis, J., Varghese, R., Hayashi, B., Jain, A., & Laporte, D. (2022). Evaluation of a Slipped Capital Femoral Epiphysis Virtual Reality Surgical Simulation for the Orthopaedic Trainee. Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews, 6(4), e22.00028. DOI:
  • Moorhouse, B., Kohnke, L. (2022) Conducting formative assessment during synchronous online lessons: university teachers’ challenges and pedagogical strategies. Pedagogies: An International Journal, DOI: 10.1080/1554480X.2022.2065993
  • Pappano, L. (2012). The Year of the MOOC. The New York Times. Retrieved July 19, 2022 from:
  • See, B., Gorard, S., Lu, B., Lan, D., Siddiqui, N. (2021) Is technology always helpful?: A critical review of the impact on learning outcomes of education technology in supporting formative assessment in schools, Research Papers in Education, DOI: 10.1080/02671522.2021.1907778
  • Spady, W, Australian Curriculum Studies Association. (1993). Outcome-based education.  Belconnen, A.C.T :  Australian Curriculum Studies Association.
  • Tahir, I., Van Mierlo, V., Radauskas, V., Yeung, W., Tracey, A., da Silva, R. (2022). Blended learning in a biology classroom: Pre-pandemic insights for post-pandemic instructional strategies. FEBS open bio, 12(7), 1286–1305. DOI:
  • The Franklin Institute. (2022). What is Augmented Reality? Retrieved July 20, 2022 from:
  • Vielma, K., Brey, E.M. (2021). Using Evaluative Data to Assess Virtual Learning Experiences for Students During COVID-19. Biomed Eng Education 1, 139–144. DOI:
  • Wang, P. (2015). Assessment of Asynchronous Online Discussions for a Constructive Online Learning Community. International Journal of Information and Education Technology, Vol. 5, No. 8. Accessed July 18, 2022 from
  • Warden, C. A., Stanworth, J. O., Ren, J. B., Warden, A. R. (2013). Synchronous learning best practices: An action research study. Computers & Education, 63, 197–207. DOI: doi:10.1016/j.compedu.2012.11.010.
  • Zi Yan, Ziqi Li, Ernesto Panadero, Min Yang, Lan Yang & Hongling Lao (2021) A systematic review on factors influencing teachers’ intentions and implementations regarding formative assessment. Assessment in Education: Principles, Policy & Practice, 28:3, 228-260, DOI:

Newsletter & Conference Alerts uses the information to contact you about our relevant content. For more information, check out our privacy policy.