Bedoya-Valencia, L., & Correa-Martinez, Y., & Palacio, K. S., & Guzman Acuña, L. (2019, June), Designing Blended Content Modules as Support to Traditional Face-to-Face Delivery: An Application to Data Analysis, Inferential Statistics, and Simulation Experiments Courses  Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32619

\bibitem{asee_peer_32619}
  Bedoya-Valencia, L., \& Correa-Martinez, Y., \& Palacio, K. S., \& Guzman Acuña, L. (2019, June), \emph{Designing Blended Content Modules as Support to Traditional Face-to-Face Delivery: An Application to Data Analysis, Inferential Statistics, and Simulation Experiments Courses}
  Paper presented at 2019 ASEE Annual Conference \& Exposition , Tampa, Florida.
  10.18260/1-2--32619

Leonardo Bedoya-Valencia, Yaneth Correa-Martinez, Katherine Sofía Palacio, and Luceny Guzman Acuña.  "Designing Blended Content Modules as Support to Traditional Face-to-Face Delivery: An Application to Data Analysis, Inferential Statistics, and Simulation Experiments Courses".  2019 ASEE Annual Conference & Exposition , Tampa, Florida, 2019, June.  ASEE Conferences, 2019.  https://peer.asee.org/32619 Internet.  25 Apr, 2024

\bibitem{asee_peer_32619}
  Leonardo Bedoya-Valencia, Yaneth Correa-Martinez, Katherine Sofía Palacio, and Luceny Guzman Acuña.
  "Designing Blended Content Modules as Support to Traditional Face-to-Face Delivery: An Application to Data Analysis, Inferential Statistics, and Simulation Experiments Courses".
  \emph{2019 ASEE Annual Conference \& Exposition , Tampa, Florida, 2019, June}.
  ASEE Conferences, 2019.
  https://peer.asee.org/32619 Internet.  25 Apr, 2024

@INPROCEEDINGS{asee_peer_32619
author = "Leonardo Bedoya-Valencia, Yaneth Correa-Martinez, Katherine Sofía Palacio, and Luceny Guzman Acuña"
title = "Designing Blended Content Modules as Support to Traditional Face-to-Face Delivery: An Application to Data Analysis, Inferential Statistics, and Simulation Experiments Courses"
booktitle = "2019 ASEE Annual Conference \& Exposition "
year = "2019"
month = "June"
address = "Tampa, Florida"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/32619}
number = {10.18260/1-2--32619}
}

TY  - CPAPER
AB  - Due to the boom in technological innovations and the accessibility to web-assisted tools, blended instructional environments have dramatically increased the options for content delivery in nontraditional formats.  While several questions have arisen regarding the benefits and pedagogical challenges of blended instructional models, the use of these environments has quickly spread across higher education.  Programs have adopted blended learning environments mainly due to three reasons: 1) improved pedagogy, 2) increased access/flexibility, and 3) increased cost effectiveness.  The Industrial Engineering Department at a large private university in Colombia and the Engineering Department and the School of Business at a regional comprehensive university in the United States have been transitioning and incorporating web-assisted tools into three courses.  This work focuses on the designing, implementation, and assessment stages of blended modules containing theoretical content, common to all of the courses, in order to support Face-to-Face delivery.
This paper presents the process of designing and assessing web-based modules to support the traditional Face-to- Face delivery of the theoretical aspects of two discrete and two continuous distributions.  Both are core concepts to the Data Analysis and Simulation Experiments courses taught to juniors in the Bachelor of Science in Industrial Engineering (BSIE) and Inferential Statistics course taught to all sophomores in the School of Business.  Once the concepts and theoretical aspects have been introduced to the students, the courses proceed to introduce diverse applications of the distributions into both manufacturing and service systems.  Two of the main students’ complaints about the delivery of these concepts are the pace and scope of the Face-to-Face delivery.  In this proposed blended format, students on all of the courses will be presented with the concepts and exercises about the mentioned statistical distributions, before the Face-to-Face session in a self-timed delivery mode.  In order to assess if this blended format increases the understanding about both the discrete and continuous distributions, three control and three experimental groups will be evaluated.  The control groups, one on each course, will not have access to the blended modules.  Both set of groups will be evaluated and compared by using tests and homework assignments.

AU  - Leonardo Bedoya-Valencia
AU  - Yaneth Correa-Martinez
AU  - Katherine Sofía Palacio
AU  - Luceny Guzman Acuña
CY  - Tampa, Florida
DA  - 2019/06/15
PB  - ASEE Conferences
TI  - Designing Blended Content Modules as Support to Traditional Face-to-Face Delivery: An Application to Data Analysis, Inferential Statistics, and Simulation Experiments Courses
UR  - https://peer.asee.org/32619
DO  - 10.18260/1-2--32619
ER  -