Ppsychometrics를 활용한 신뢰성있는 인지부하 측정: 객관적인 교육프로그램 최적화 모델(Med Educ, 2016)

Ppsychometrics를 활용한 신뢰성있는 인지부하 측정: 객관적인 교육프로그램 최적화 모델(Med Educ, 2016)

Reliable cognitive load measurement using psychometrics: towards a model of objective teaching programme optimisation

K. H. Vincent Lau & Jeremy Moeller

CLT의 구인과 측정에 대해서 Young and Sewell은 psychometrics의 역할을 주장함.

In their 2015 review detailing the challenges of construct and mea- surement in cognitive load theory (CLT), Young and Sewell pro- posed the role of psychometrics in the more reliable measurement of cognitive load (CL).1

 

Sewell 등은 "만약 어떻게 피훈련자가 working memory resources를 사용하는지 이해한다면, CL이 불균형을 이루거나 과도한 영역을 찾아낼 수 있을 것이고, 그 영역이 바로 학습에 제한을 가져오고 환자에 대한 harm의 위함이 증가하는 영역일 것이다"

Sewell et al. summarise the practical applica- tion as: ‘...if we understand how trainees are using working mem- ory resources, we can identify areas in which CL is imbalanced or overwhelming – areas in which learning is limited and risk of harm to patients increases.’2

간단히 말해서 CLT는 작업기억이 학습의 주요 제한요인이라고 하는 이론이며, 세 하위유형으로 구분한다.

Briefly, CLT posits that working memory is the major limiting fac- tor in learning and divides CL into three subtypes:

• intrinsic load (IL), which relates to the inherent diffi- culty of the learning task; 
  과제 자체의 내재한 난이도
• extraneous load (EL), which relates to teaching techniques and the envi- ronment, and
  교육 테크닉과 환경과 관련
• germane load (GL), which relates to the student’s use of deliberate strategies to enhance meaningful learning.
  유의미한 학습을 향상시키기 위한 학생의 전략

 

CL 하위유형을 측정하는 목적은 교육프로그램을 adjust하여 distraction을 최조화시켜 EL을 낮추는 것이다.

The purpose of measuring CL subtypes is to adjust a teaching programme through iterations by, for example, lowering EL by minimising distractions.

Sewell 은 한 연구에서 자기보고식의 19문항짜리 CL 하위유형 측정 도구를 개발하였다.

In this study, Sewell et al. developed a self-report, 19-itempsychometric tool that reliably measures CL sub- types in colonoscopy.2

이 연구에서 GL은 CL의 하위유형이라는 근거를 제시했지만, 모든 전문가가 이를 인정하는건 아니다. 

The study also provides evidence that GL is a distinct CL subtype, a view not shared by all experts in the field.3

CLT가 지난 수십년간 잘 성립되었고 널리 퍼졌지만 CL을 측정하려는 노력은 중간 정도의 성공만 거두었을 뿐이다. 일반적으로 말해서, IL은 여러 점수체계간 상관관계가 높지만 EL과 GL은 좀 더 elusive하다.

Whereas CLT has been well estab- lished over a few decades and widely applied, efforts to measure CL have seen only moderate suc- cess. In general, IL is most reliably quantified with reasonably high degrees of correlation between different scoring systems,9 whereas EL and GL are more elu- sive.4,9

CL 측정도구를 더 발전시켜야 한다. 가장 최근의 연구는 2013년의 trial이다.

In this context, there was a need for further development of CL measurement tools using rigorous qualitative and quantitative meth- ods. The most recent and notable study is a 2013 trial examining CL in a university statistics course,11

CL을 낮추는 것은 post-test에서 더 나은 수행능력과 관련있었다.

It also demonstrated that decreasing CL was associated with better performance in a post-test.11

이 연구에서는 CL 측정의 실현가능성 뿐 아니라, 측정도구 개발의 섬세한 디테일까지 묘사하였다. 

Importantly, this study2 not only demonstrates the feasibil- ity of measuring CL, but describes in elegant detail the development of the measuring tool, providing a guide for future similar efforts.

CBTM와 같은 high-impact 교육세팅에 있어서 validated CL측정도구는 반복과 리모델링을 통하여 최적화될 수 있을 것이다. 그러한 프로그램을 개발하려면 다음이 필요하다.

in specific high-impact education settings like dissemi- nated multi-institution pro- grammes such as in CBTMs(computer- based teaching modules (CBTMs)), a validated tool for CL measure- ment will allow for optimisation through iterations and remod- elling. The development of such a programme may involve:

• (i) identifying a well-defined and manageable learning setting (with complexity on the order of colo- noscopy teaching);
• (ii) developing and validating a self-report tool to measure CL for this setting;
• (iii) seeking additional validation by selecting a representative subset of subjects to undergo non-self- report external assessment such as by secondary task performance, and
• (iv) optimising CL subtypes through iterative changes.

더 넓은 맥락에서 이 연구는 실시간학습의 측정에 psychometrics를 적용할 수 있다는 것을 validate하였다. 재생산가능한 결과를 보여줌으로써 저자들은 학습자들이 기존에 생각했던 것보다 더 나은 reporter가 될 수 있으며, 자기보고로 수집한 데이터가 쉽사리 평가절하discredited 되지 말아야 한다고 주장했다.

In a broader sense, the study also validates psychometrics in its new application to the measurement of real-time learning. By demonstrat- ing reproducible results, the authors suggest that learners may be better reporters than previously thought, and data obtained from self-report should not be easily discredited in educa- tion research.2

13 van Merrie¨nboer JJG, Sweller J. Cognitive load theory in health professional education: design principles and strategies. Med Educ 2010;44 (1):85–93.

14 Lau KHV. Computer-based teaching module design: principles derived fromlearning theories. Med Educ 2014;48 (3):247–54.

15 Qiao Y, Shen J, Liang X, Ding S, Chen F, Shao L, Zheng Q, Ran Z. Using cognitive theory to facilitate medical education. BMC Med Educ 2014;14:79.

17 Jelovsek JE, Kow N, Diwadkar GB. Tools for the direct observation and assessment of psychomotor skills in medical trainees: a systematic review. Med Educ 2013;47 (7):650–73.

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Med Educ. 2016 Jun;50(6):606-9. doi: 10.1111/medu.13046.

Reliable cognitive load measurement using psychometrics: towards a model of objective teachingprogramme optimisation.

Lau KH1, Moeller J1.

Author information

• 1New Haven, Connecticut, USA.

PMID:

 

27170078

 

DOI:

 

10.1111/medu.13046

[PubMed - in process]