A web-based learning tool improves student performance in statistics: A randomized masked trial

Background: e-status is a web-based tool able to generate different statistical exercises and to provide immediate feedback to students' answers. Although the use of Information and Communication Technologies (ICTs) is becoming widespread in undergraduate education, there are few experimental studies evaluating its effects on learning. Method: All of the students (121) from an introductory course for statistics in dentistry were randomly assigned to use the tool with one of two 6-problem sets, known as types A and B. The primary endpoint was the grade difference obtained in the final exam, composed of two blocks of questions related to types A and B. The exam evaluator was masked to the intervention group. Results: We found that the effect of e-status on the student grade was an improvement of 0.48 points (95% CI: 0.10-0.86) on a ten-point scale. Among the 94 students who actually employed e-status, the effect size was 0.63 (95% CI: 0.17-1.10). Conclusions: It is feasible to formally assess the learning effect of an innovative tool. Providing e-status exercises to students has a direct effect on learning numerical operations related to statistics. Further effects on higher cognitive levels still have to be explored.

[1]  D Moher,et al.  The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomized trials. , 2001, Annals of internal medicine.

[2]  Erica Morris.  The design and evaluation of Link: A computer-based learning system for correlation , 2001, Br. J. Educ. Technol..

[3]  Mary Peat,et al.  Managing change: The use of mixed delivery modes to increase learning opportunities , 2001 .

[4]  M. Oliver,et al.  Evaluating web-based learning modules during an MSc programme in dental public health: a case study , 2002, British Dental Journal.

[5]  H. Mandl,et al.  The effects of cooperative learning and feedback on e-learning in statistics , 2009 .

[6]  Beth Chance,et al.  Components of Statistical Thinking and Implications for Instruction and Assessment , 2002 .

[7]  Martin Oliver,et al.  Evidence‐based practice and e‐learning in Higher Education: can we and should we? , 2003 .

[8]  H. Simons.  Evidence‐based practice: panacea or over promise? , 2003 .

[9]  Ivo D. Dinov,et al.  Pedagogical utilization and assessment of the statistic online computational resource in introductory probability and statistics courses , 2008, Comput. Educ..

[10]  José A. González,et al.  e‐status: An automatic web‐based problem generator—Applications to statistics , 2006, Comput. Appl. Eng. Educ..

[11]  Slavomir Stankov,et al.  Controlled experiment replication in evaluation of e-learning system's educational influence , 2009, Comput. Educ..

[12]  Jean Underwood,et al.  Integrated learning systems in the classroom , 1999, Comput. Educ..

[13]  R. Horton,et al.  Common sense and figures: the rhetoric of validity in medicine (Bradford Hill Memorial Lecture 1999). , 2000, Statistics in medicine.

[14]  Jürgen Symanzik,et al.  Teaching Experiences With a Course on “Web-Based Statistics” , 2003 .

[15]  Reidar Hagtvedt,et al.  Teaching Confidence Intervals Using Simulation , 2008 .

[16]  Lisa J. Carnell.  The Effect of a Student-Designed Data Collection Project on Attitudes Toward Statistics , 2008 .

[17]  Graham Alsop,et al.  From Effect to Effectiveness: The Missing Research Questions , 2007, J. Educ. Technol. Soc..

[18]  Scott R. Evans,et al.  Evaluation of Distance Learning in an "Introduction to Biostatistics" Class: A Case Study , 2007 .

[19]  Miguel Nussbaum,et al.  Methodology for evaluating a novel education technology: a case study of handheld video games in Chile , 2006, Comput. Educ..

[20]  Jorge Larreamendy-Joerns,et al.  Six Online Statistics Courses: Examination and Review , 2005 .

[21]  Barbara Means,et al.  Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies , 2009 .

[22]  Ramazan Basturk,et al.  The Effectiveness of Computer-Assisted Instruction in Teaching Introductory Statistics , 2005, J. Educ. Technol. Soc..

[23]  Tony Fisher,et al.  ImpaCT2: the impact of information and communication technologies on pupil learning and attainment , 2002 .

[24]  Heinz Mandl,et al.  Supporting learning using external representations , 2008, Comput. Educ..

[25]  Diana Elbourne,et al.  Improving the Usability of Educational Research: Guidelines for the REPOrting of Primary Empirical Research Studies in Education (The REPOSE Guidelines) , 2004 .

[26]  Dani Ben-Zvi,et al.  How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics , 2007 .

[27]  Heidi S Chumley-Jones,et al.  Web‐based Learning: Sound Educational Method or Hype? A Review of the Evaluation Literature , 2002, Academic medicine : journal of the Association of American Medical Colleges.

[28]  D. Moher,et al.  The Revised CONSORT Statement for Reporting Randomized Trials: Explanation and Elaboration , 2001, Annals of Internal Medicine.

[29]  Fernando Alonso,et al.  An instructional model for web-based e-learning education with a blended learning process approach , 2005, Br. J. Educ. Technol..

[30]  The periodic health examination. Canadian Task Force on the Periodic Health Examination. , 1979, Canadian Medical Association journal.

[31]  D. Moher,et al.  The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomised trials , 2001, The Lancet.