Optimal scaffolding method for resume writing in the supplementary online writing course

ABSTRACT

Many studies have measured the effects of separate scaffolding methods for online learning, but the various methods are seldom directly compared to provide concrete teaching suggestions. This study aims to investigate the effects of three popular scaffolding methods on students’ ability to obtain resume standards, course satisfaction and engagement in an online resume writing course. Sixty-eight mixed-major undergraduate students in a private four-year college in Central Taiwan watched video lectures embedded in video-viewing Google forms before section writing. The comparison video (V) group did not receive extra support while three treatment groups (section quiz (SQ), writing rubric (WR) and peer-feedback (PF) groups) were offered scaffolding emphasizing resume genre features. The data derived from surveys and writing samples revealed that over the four-week treatment, the PF group was consistently more attentive to the organization genre standards than the other groups but performed similarly to the SQ group on grammar features. Although all groups expressed satisfaction with the course, they varied in engagement levels. The PF group reported considerably lower engagement than the SQ and V groups. The WR group was low in both writing and engagement. Therefore, the combination of scaffolding methods is recommended for implementation.

KEYWORDS:

• Online writing course
• scaffolding
• peer-evaluation
• writing rubrics
• video lectures
• genre adherence

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Ministry of Science and Technology of Taiwan, Republic of China (MOST 108-2511-H-011-002-MY4), FinCEAL Plus (51770), and the Academy of Finland (318380).

Notes on contributors

Alexandra Zakharova

Alexandra Zakharova is a doctoral student in the Graduate Institute of Digital Learning and Education at National Taiwan University of Science and Technology (NTUST) and a Special Program Instructor at Ming Chuan University (MCU), Taiwan. Her research interests lie in the area of blended and autonomous learning, collaborative writing as well as technology-assisted language learning.

Katerina Evers

Katerina Evers is a doctoral student in the Graduate Institute of Digital Learning and Education at NTUST, Taiwan. Her research interests include mobile learning, flipped classroom, multimedia design, and language learning with digital technology.

Sufen Chen

Sufen Chen is a chair professor in the Graduate Institute of Digital Learning and Education at NTUST, Taiwan, and extraordinary professor in the Optentia Research Focus Area at North-West University, South Africa. She received her BS and MS in physics from National Taiwan University and PhD in science education from Indiana University-Bloomington. Her research interests are in the area of science education, technology-enhanced learning, metacognition, achievement emotions, and social media. Dr. Chen has published in Computer Assisted Language Learning, Journal of Research in Science Teaching, Computers & Education, Science Education, Physical Review Physics Education Research, New Media & Society, Computers in Human Behavior, International Journal of Information Management, and Journal of Computer Assisted Learning, among others.