the impact of lecture webcasts and student self-regulated learning on academic outcomes
DESCRIPTION
The growth of online technologies and their incorporation into learning environments is based on the expectation that including technologically-based supportive tools into a blended learning environment will substantially improve students\’ learning outcomes. However, very little is known about the motivational, cognitive, and behavioural self-regulation attributes that may contribute to student success in blended learning. Using a social cognitive view of selfregulated learning as a theoretical framework (Pintrich, 1999, 2004; Zimmerman, 1989,1998,& 2002) the present study examined the relations between students\’ self-regulation attributes and their academic outcomes in a blended learning course that provided the webcast recording of the face-to-face lectures, online access to weekly quizzes and course assignment and question/discussion boards. Additionally, this study examined whether webcast viewing was associated with students` academic outcomes in the course. A small, but significant positive correlation was found between students\’ overall viewing times and their academic outcomes in the course. Students were generally more likely to view the webcasts either immediately after the weekly lecture or on the days immediately preceding their scheduled exam in the course. An exploratory path analysis indicated that intrinsic goal orientation, time and environment management, effort regulation, and self-efficacy had significant impacts on students’ final grades. Students with low self-regulation skills could benefit from webcasts as long as they were driven by intrinsic rewards and could direct their efforts to the task at hand.TRANSCRIPT
The Impact of Lecture Webcasts and Student Self-Regulated LearningOn Academic Outcomes
Nima Hejazifar, M.Sc.
Applied Modelling and Quantitative Methods
Trent University
This talk presents an exploratory model of self-regulation in a blended learning environment
1. Blended Learning 2. Self-Regulated Learning
3. Evaluation of Blended Learning at Trent University
4. The Exploratory Model of Self-Regulation and Webcasting
Online
Face to Face
Blended Learning+
Forethought Phase
Performance Phase
Self-Reflection
Phase
Motivational Factors
Cognitive Factors
Behavioural Factors
Webcast Viewing
Final Grades
Online learning
Face to face learning
+
Blended learning is the combination of online and face-to-face learning
Blended learning 30 to 79% of the contents
online
80+% of the contents online
traditional or web facilitated (1 to 29% of the contents online)
Online learning
Face to face
learning
+Blended learning
It is very important for instructors to have a clear objective when introducing blended learning to students
Categories of Blended Learning
Enabling blends
Enhancing blends
Transforming blends
Blended learning provides the best of both worlds
Online learning
Face to face
learningBlended learning
Control the pacing and location of learning
Flexibility to Review material
Advantages
DisadvantageProcrastination
Using the social cognitive view of self-Regulated learning to examine academic performance in a blended setting
Performance Phase
Self-Control
Self-Observation
Forethought Phase
Self-motivation beliefs
Task analysis
Self-reflection Phase
Self-judgment
Self-reaction
Forethought Phase refers to processes that take place before efforts to learn
Forethought PhaseTask Analysis
Goal SettingStrategic planning
Self-Motivation Beliefs Self-efficacy
Outcome expectation Intrinsic interest/value
Learning goal orientation
Forethought Phase
Performance Phase
Self-Reflection Phase
Forethought Phase
Performance Phase
Self-Reflection Phase
Performance PhaseSelf-Control
ImagerySelf-instruction
Self-Observation
Self-experimentation Self-recording
Attention focusing Task strategies
Performance phase refers to the processes that take place during the application of behaviour
Self-reflection phase refers to processes that take place after each learning effort
Forethought Phase
Performance Phase
Self-Reflection Phase
Self-Reflection PhaseSelf-judgment Self-evaluation
Causal attributionSelf-Reaction
Adaptive/defensive Self-satisfaction/affect
To date, four specific self-regulatory dimensions are known to play a role in blended settings
Intrinsic goal orientation
Self-efficacy
Time and environment management
Help seeking
Webcast was selected as the primary online tool for the introduction to psychology blended course at Trent University
Methodology
451 students (340 female and 111 male)
Participants
Measures
Motivated Strategies for Learning Questionnaire (MSLQ)
Participants’ viewing time for each lecture
Final grade in the course
Students viewed the webcasts either immediately after the lectures or a few days prior to the final exam
Webcast Viewing and Academic Outcome
Students welcomed the addition of webcasts into the course
Overall, webcast viewing was significantly and positively associated with students’ academic outcomes
This study was one of the first studies to explore the role previously unexplored self-regulatory variables in a blended learning course
Effort regulation
Peer learning
Test anxiety
Task value
Task value
Intrinsic
Self-efficacy
Manage
Effort
Help-seeking
Peer learning
Test anxiety
Overall viewing
Final grade
-.06-.07
.37*** .16*
-.32***
.33***
-.09
-.09
-.05
.28***
.09 .84*
Solid Lines Represent Significant Path Coefficients. Dashed lines Depict Significant Correlations When No Significant Path Coefficients Exist., *p < 0.05; **p < 0.01; ***p < 0.001.
This study is an important addition to the very limited but growing field of research examining self-regulated learning in blended learning environments
Motivational Factors
Cognitive Factors
Behavioural Factors
Webcast Viewing
Final Grades
Low SRL can benefit if they direct effort and are driven by intrinsic rewards
Students view immediately after lecture or a few days before exam
Questions?
References
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41, 64-70.
Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16, 385-407.
Pintrich, P. R., Smith, D. A. F., Garcia, T., & Mckeachie, W. L. (1993). Reliability and predictive validity of the motivated strategies for learning questionnaire (MSLQ). Educational and Psychological Measurement, 53, 801-813.
Allen, I. E., & Seaman, J. (2010). Learning on demand: Online education in the United States, 2009. Needham, MA: Sloan Center for Online Education.
Graham, C. R. (2006). Blended learning systems: Definition, current trends, and future directions. In C. Bonk & C. Graham (Eds.), The Handbook of Blended Learning: Global perspectives, local designs. San Francisco, CA: Pfeiffer
Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45, 166-183.