Mastery-based learning literature by Tina Chargois, iNACOL intern

Today’s post is by one of iNACOL’s Research Interns, Tina Chargois. She did a miniature literature review on mastery-based learning. For more information about Tina, please see her bio on our Research Resources and Initiatives page. If you have feedback for Tina, please leave it as a comment below or email her directly at [email protected]. Thanks, and enjoy!

Mastery Learning and Technology

A Literature Review

By Tina Chargois

“Mastery is not something that strikes in an instant, like a thunderbolt,

but a gathering power that moves steadily through time, like weather.”

― John Gardner (2010, p. 15)

            Mastery learning is a concept developed by Bloom in the 1960’s in an effort to address the limitations of the traditional teacher-centered learning environment (Bloom, 1968).  Block and Burns (1976) offer the following definition for mastery learning:  “Essentially this philosophy asserts that under appropriate instructional conditions virtually all students can learn well, that is, can “master,” most of what they are taught” (p. 3).   It is believed that this systematic way of teaching allows students to master basic skills which can be built upon in subsequent learning environments (Block & Burns, 1976).  Mastering learning objectives builds the confidence necessary for students to have the desire to build upon their current skills and further their knowledge acquisition (Block & Burns, 1976).

Mastery learning is an approach to the design of classroom learning based on philosophies of education that are many times considered controversial.  There are two distinct sides of the philosophical views of the effects of the mastery learning approach to education.  There are some that view mastery learning strategies as a form of instruction that is too inflexible and systematic (Groff, 1974).  There is the belief that mastery learning only affords students basic skills necessary for navigation of a rigid society (Cronbach, 1972).  With this argument, critics of mastery learning argue that teachers who adhere to the mastery learning approach to instruction do not appreciate the multidimensionality of the learning process (L. S. Bowen, 1975).  Advocates of mastery learning argue that this approach to learning is indeed a multifaceted, adaptable educational strategy (Levin, 1974; Scriven, 1975).  Their belief is that mastery learning offers students the skills necessary to thrive in an ever-changing society while keeping in mind the realities of the classroom environment. (H. M. Levin, 1975; Block & Anderson, 1975).

There are two basic categories of mastery learning.  The first of which is Bloom’s (1968) Learning for Mastery (LFM) strategy which evolved from the field of education and is implemented mainly in elementary and secondary school settings.  Some of the basic features of the LFM model were outlined by Bloom (McNeil, 1969):

1. The learner should have an understanding of the task and the procedures necessary for completing the task.
2. It is important to formulate specific objectives for the task to be learned.
3. The course subjects should be broken down into smaller units of learning, and the learner should be tested after each unit.
4. The instructor should give the learner feedback on particular errors after each test.
5. The instructor should find ways to give the learner additional time when needed.
6. Providing alternative learning opportunities could prove to be gainful.
7. Learners working in cooperative group settings for more than an hour, with the focus of reviewing test results can increase student effort.

The other major mastery learning strategy is the Personalize System of Instruction (PSI). This approach to mastery learning evolved from the field of psychology and was developed by John B. Carroll (1963, 1965).  It is mostly implemented at the university level, and easily lends itself to the use of technology as a means of accomplishing mastery learning goals.  Technology allows for the differentiation and individualized learning that comprise the major components of the PSI approach to mastery learning described by Hartly (1974):

1. The learner should be given well defined goals.
2. The instruction should be delivered in sequential steps that build towards the instructional goal.
3. The learner should be allowed to work at his own pace.
4. The learner should be encouraged to fully participate in each step of the learning process.
5. The learner should be given immediate feedback regarding their performance and participation.

The argument of the opponents to this instructional approach state that this mode of instruction is geared more toward teaching individual students rather than whole-class learning.  It is also argued that the “small steps” approach to learning does not correlate to the “large steps” manner in which learning takes place in the classrooms, and it does not take into account the personal-social element of classroom learning. Technology has been found to help address some of the concerns raised by critics of mastery learning (Boggs, Shore and Shore, 2004). There are several studies that have combined the use of mastery learning strategies with educational technology for the purpose of increasing student academic achievement.

In an effort to close the achievement gap between lower achieving and higher achieving students in mainstream secondary math courses, Hoon, Chong, and Binti Ngah (2010) conducted research comparing the results of the use of Computer-assisted Cooperative Learning (CCL), Computer-assisted Mastery Learning (CML) and Computer-assisted Cooperative Mastery Learning (CCML) strategies.  The researchers studied 262 secondary math students.  The data was collected to determine the effectiveness of each computer assisted learning strategy on the students’ gain scores and their time-on-task.  The research study determined that the CCL strategy was not as effective as the other two strategies, and the CCML learning strategy produced the most gains in student scores.  The students also spent more time on task when participating in the CCML learning strategy as compared to the other two.  In particular, as it relates to mastery learning, the Computer-assisted Mastery Learning (CML) proved to be the most effective strategy of the three for improving the lower performing students’ gain scores.  This study demonstrates that combining mastery learning with multimedia tools and cooperative learning strategies can prove to be an effective combination in facilitating the learning process (Hoon et. al., 2010).

Borton (1988) attempted to determine the effectiveness of using computers to manage individualized instruction within a mastery learning design. The study utilized an ex-post-facto, quasi-experimental design with a sample of 92 fifth grade students. The control group was comprised of both third through fifth grade mathematics students’ scores and the two preceding fifth grade students’ scores.  The students in the treatment group were delivered math lessons through individualized and teacher-delivered computer-managed instruction.  The treatment group scored significantly higher than the combined control groups. The results of this study found that individualized and teacher-delivered computer-managed instruction resulted in higher achievement than previous fifth grade students without individualized and teacher-delivered computer-managed instruction (Borton, 1988).

Another study conducted by Lin, Liu, Chen, Liou, Chang, Wu, and Yuan (2013) utilized technology to apply mastery learning concepts to remedial mathematical instruction. The study compared the effectiveness of video-based and game-based remedial mathematics instruction on student performance. The study used a nonrandom cluster sample of 62 sixth grade students.  All participants expressed interest in receiving remedial math instruction.  The students were divided into two groups based on their average pretest scores. The control group used instructional videos and experimental group used educational games.  The learning material was divided into small components, and students were able to monitor their own learning based on ongoing analytical feedback related to their learning outcomes.  This study substantiated the effectiveness of using computer games or videos in mathematics learning environments. It was also found that a combination of mastery learning instruction with game-based learning strategies provides greater achievement for math students.  This study substantiated the effectiveness of using computer games or videos in mathematics learning environments (Lin et. al., 2013).

Bloom and Carroll could not have imagined in the 1960’s that  there would be an educational platform which would allow students to work at their own pace, the opportunity to master small sections of content, and immediate feedback on tests, all delivered by way of computers.   A fresh perspective on mastery learning coupled with the endless possibilities that virtual education has to offer can afford students the opportunity for true mastery of content.  Research has proven that computer assisted instruction through gaming and blended education enables teachers to employ more mastery learning strategies. Virtual education has the potential to embody the “appropriate instructional conditions” that Block and Burns (1976) referred to in their definition of mastery learning.

References

Block, J. H. & Anderson, L. W. (1975).  Mastery learning in classroom instruction.  New York:  Macmillan.

Block, J. H., & Burns, R. B. (1976). Mastery learning. Review of Research in Education, 4, 3-49.              Retrieved from http://faculty.unlv.edu/jensen/html/Doctorate/CIT620/materials/block_burns_1976.pdf

Bloom, B. S. (1968). Learning for mastery. Evaluation Comment, 1(2), 1-5.

Boggs, S., Shore, M., & Shore, J.A. (2004). Using e-Learning platforms for mastery learning in developmental mathematics courses. Mathematics and Computer Education. 38(2), 213-220.

Borton, W. M. (1988). The effects of computer managed mastery learning on mathematics test scores in the elementary school. Journal of Computer-Based Instruction, 6(3), 311-328.

Bowen, L.S. (1975). Book review of block. J. H. (Ed.) Schools, Society, and Mastery Learning. Educational Forum. 49, 251-252.

Carroll, J. (1963).  A model of school learning.  Teachers College Record. 64, 723-763.

Carroll J. (1965).  School learning over the long haul.  In J.D. Krumboltz (Ed.) Learning and the Educational Process.  Chicago:  Rand McNally.

Cronbach, L. J. (1976).  How can instruction be adapted to individual differences? In R. Gagne’ (Ed.) Learning and Individual Differences. Columbus, Ohio: Charles E. Merrill.

Gardner, J. (2010). The art of fiction: Notes on craft for young writers. Random House Digital, Inc..

Groff, P. (1974).  Some criticisms of mastery learning. Today’s Education, 63, 88-91.

Guskey, T. R., & Gates, S. L. (1986). Synthesis of research on the effects of mastery learning in elementary and secondary classroom. Educational Leadership, 43(8), 73-80.

Hartley, J. (1974). Programmed instruction 1954-1974:  A review.  Programmed Learning and Educational Technology, 11, 278-291.

Hoon, T. S., Chong, T. S., & Binti Ngah, N. A. (2010). Effect of an Interactive Courseware in the Learning of Matrices. Educational Technology & Society, 13 (1), 121–132.

Levin, H. M. (1974).  The economic implications of mastery learning.  In J. H. Block (ed.), Schools Society and Mastery Learning.  New York:  Holt Rinehart & Winston.

Levin, H. M. (1975). An economic view of education for health professions.  Paper prepared for the Invitational Conference on Flexible Education for the Health Professions, University of Iowa, Iowa City.

Lin, C-H., Liu, E. Z.-F., Chen Y.-L., Liou, P.-Y., Chang, M., Wu, C.-H., Yuan, S.-M. (2013).  Game-based remedial instruction in mastery learning for upper-primary school students. Educational Technology & Society, 16 (2), 271–281.

McNeil, J. D. (1969).  Forces influencing curriculum. Review of Educational Research, 39, 293-318.

Scriven, 1975.  Programmed instruction 1954-1974: A review.  Programmed Learning and Educational Technology, 11, 278-291.