4차 산업혁명 시대에 새로운 환경의 변화에 유연하게 대처하기 위해 새로운 사고 및 행동방식의 빠른 습득이 요구되고, ‘지식의 반감기’로 지식이 폐기되는데 걸리는 시간이 짧아지기 때문에 학습민첩성은 최근에 더 주목을 받게 되었다. 육군비전 2050에서 우리 군은 미래 육군을 위한 역량으로 기민성(agility) 등 5가지를 제시하였고, 리더십 모형에서도 기민한(agile) 작전수행 분야에서 정신적 민첩성(mental agility)을 강조하며 학습민첩성의 초기개념을 일부 차용하였지만, 현재의 발전된 개념을 적용하고 있지는 못하는 듯하다. 미래 전장에서 ‘시간과 공간을 주도하는 초일류 육군’을 육성하는데 기여하기 위해, 학습민첩성에 대한 선행 및 결과변인, 그리고 조절변인을 연구하였다. 학습민첩성이 초래하는 결과가 긍정적이라면 그 필요성이 증명될 것이고, 학습민첩성에 영향을 주거나 조절하는 요인은 학습민첩성의 향상방안을 시사해 줄 것이기 때문이다.
먼저, 지금까지 연구된 이론과 선행연구를 망라하여, 학습민첩성 개념과 모델, 측정도구, 변인으로 나누어 살펴보았고, 특히 변인은 선행, 결과, 조절변인으로 분류하여 고찰하였다. 그 결과 세 가지 선행변인(직무특성, 개인특성, 조직특성)과 결과변인(혁신행동), 조절변인(직속상관의 학습몰입리더십)을 도출한 후 10개의 연구가설과 3개의 연구모형 및 56개의 진단문항을 선정하였다. 학습민첩성의 개념모형과 진단문항은 기존의 다차원적 접근과 단차원적 접근의 논란을 해소할 수 있도록 맥락적으로 접근하여 개발한 박정열(2019)의 것을 사용하였다. 예비조사는 ‘20년 5월 군 장병 126명을 대상으로 실시하여, 군인들의 이해가 어려운 20개 문항을 검토하여 보완하였고, 조사대상은 군에 대해 이해가 깊은 5년차 이상 전투병과 위주의 장교와 부사관으로 선정하였다.
본조사는 431명을 대상으로 ‘20년 8월 한달간 설문지를 배부하고 회수하였으며, 불성실한 답변자 6명을 제외하고 425명을 대상으로 분석하였다. 자료분석을 위해 기술통계분석을 시행한 후, 구조방정식 모델의 2단계 모형추정 가능 절차를 실시하였다. χ2(CMIN), TLI, CFI, SRMR 및 RMSEA 지수로 측정모형의 적합도를 확인하고, 수렴 및 판별타당도를 검증한 후 구조모형의 적합도를 확인하였다. 마지막으로 Baron & Kenny(1986)의 방법을 이용하여 위계적 회귀분석을 실시하여 조절효과를 검증하였다.
연구결과는 다음과 같다. 첫 번째, 학습민첩성은 혁신행동에 정적인 영향을 미치었으나, 학습몰입리더십의 조절효과는 없었다. 두번째, 개인특성 중 경험개방성, 학습목표지향성은 학습민첩성을 매개로 혁신행동에 정적인 영향을 주었으나, 여기에서 조절효과는 유의하지 않았다. 세번째, 직무특성 중 직무자율성과 직무도전성은 학습민첩성을 매개로 혁신행동에 정적인 영향을 주었다. 네번째, 조직특성 중 정보체계는 학습민첩성을 매개로 혁신행동에 정적인 영향을 주었으며, 여기에서 상사의 학습몰입리더십은 조절효과가 확인되었다.
본 연구의 학문적 의의는 학습민첩성을 육군에 처음 적용하여 실증연구를 하였고, 10개의 선행변인을 3개의 연구모형에 투입하여 종합적이고 세부적으로 분석하였으며, 박정열(2019)의 진단도구를 검증해 보았다는 것이다. 실무적 시사점은 육군은 미래 전장에 대비하기 위한 역량으로서 학습민첩성을 도입하여야 하고, 학습목표지향적인고 개방적인 열린 육군(Open Army)의 문화를 구축하며, 육군의 리더들은 긍정적인 실책관리문화를 바탕으로 성과보다는 직무에 대한 학습에 가치를 두도록 이끌어야 한다는 것이다.
이번 연구의 한계점과 그에 따른 후속연구 제안은 다음과 같다.
첫 번째, 자기보고식 설문의 한계를 극복하기 위해 학습민첩성의 결과변인을 객관적으로 측정할 수 있도록 360도 평가 등을 적용해 볼 필요가 있다. 둘째 장교와 부사관 신분 외에 군무원과 병 신분으로 연구대상을 확대하여 한다. 셋째 횡단적 연구의 특성을 극복하는 종단연구가 필요하며 마지막으로 학습민첩성의 하위요인까지 세분화해서 선행변인이 학습민첩성을 중심으로 매개되고 조절되어 작동하는 알고리즘에 대한 연구를 제안한다.

In the era of the 4th industrial revolution, in order to flexibly respond to changes in the new environment, it is essential to quickly learn new ways of thinking and action. Due to the increasingly shortened useful lifetime of knowledge, learning agility has been receiving more attention in recent times. Agility is one of the five suggestions of the Korean military''s Army Vision 2050, and mental agility is also emphasized in the leadership model for carrying out operations.
However, it seems that the most advanced and current concepts are not being applied. In order to foster a first class army that controls time and space in the battlefield, research on learning agility is necessary and its antecedent, moderator and result variables should be examined. If the results of learning agility are positive, its necessity will be proved, and finding a factor that influences or moderates learning agility will suggest ways of improvement.

First, covering existing theories and studies, concepts and models of learning agility, measurement tools, and variables were examined separately. In particular, variables were classified into precedence, outcome, and moderator variables. As a result, three precedence variables (job characteristics, personal characteristics, organization characteristics), one outcome variables (innovative behavior), and one moderator variables (supervisor''s learning commitment leadershi) were derived. Afterward, a preliminary survey was conducted upon selecting hypotheses, research models. The conceptual model of learning and the diagnosis questions were developed by Park, Jeongyoul & Kim, Jinmo(2019) who utilized a contextual approach to resolve the controversy between existing multi-dimensional and single-dimensional approaches. The pilot survey was conducted on 126 military personnel on May 20th. The respondents identified 20 questions that were difficult to understand and revisions were made accordingly. Regarding the subject of participants, officers and soldiers with less than 5 years of experience were excluded as were non-combatant military classes with support-orientated roles and less influence.

The main survey was conducted on 431 officers and non-commissioned officers with more than 5 years of experience, who received and completed a questionnaire during August, 2020. In total, 425 answers were analyzed, with six excluded for unscrupulous respondents. For data analysis, a descriptive statistical analysis was performed. Afterward, to verify the merriment model, a two-stage model estimation procedure of the structural equation model was conducted to evaluate the conceptual validity in parallel, and the for of the measurement model was comprehensively confirmed by x2 (CMIN), TLI, CFI, SRMR, and RMSEA index. Sequentially, the convergence validity and discriminant validity were checked, and final modifications for the structural model were made. Then, the integrity of the structural model was verified, the influence relationship between each variable was confirmed (p < .05) and the moderating effect was verified.

The research results are as follows.
First, learning agility had a positive effect on innovative behavior, but there was no moderating effect of learning commitment leadership. Second, in the first research model, openness to experience and learning goal orientation among individual characteristics had a positive effect on innovative behavior through learning agility, and the positive error management culture adjusted the effect of openness to experience on learning agility. Third, In the second study model, among job characteristics, job autonomy and job challenge had a positive effect on innovative behavior through learning agility, but the moderating effect of supervisor''s learning commitment leadership was not significant. Fourth, In the third research model, among the organizational characteristics, the information system had a positive effect on innovative behavior through learning agility, and the supervisor''s learning immersion leadership adjusted the effect of the information system on learning agility. Fifth, all three leading variables that were expected to affect learning agility partially affected it. The order of influence was personal characteristics (learning goal orientation 0.327> openness to experience 0.231)> organizational characteristics (information system 0.126)> job characteristics (job autonomy 0.118)> individual characteristics (commitment to change 0.110). In other words, in order to increase learning agility, individuals must value learning, not performance, and be open to various experiences, and an information system that can detect changes must exist and operate in the organization. It means that more authority should be given to the individuals, who should think positively and actively accept organizational change.
The limitations of this study and suggestions for subsequent studies are as follows. First, when the learning agility diagnostic tool of Park, Jeongyeol & Kim, Jinmo (2019) was applied to the group, it was found that the diagnostic items in the "experimental application" stage were extracted as the same factors as the "strategic search" items, which would hinder discriminant validity. This diagnostic tool was expected to be able to end the long debate on learning agility by analyzing it''s underlying theory and approaching it in context. However, it is necessary to be used and analyzed in various types of organizations including the military. This diagnostic tool was expected to be able to end the long debate on learning agility by analyzing it''s underlying theory and approaching it in context. However, it is necessary to be used and analyzed in various types of organizations including the military. In this study, additional research on diagnostic questions as the items in the "strategic search" stage did not fully meet the standard value for mean variance extraction. Second, in the process of verifying the structural model in which job characteristics influence the innovative behavior through learning sensitivity as a medium, the error terms of the two items of job autonomy were covariance-connected. In order to satisfy the model suitability, it was a logical connection for a revised index. Even so there may be additional problems with the independence of the two measurement items or there may be matters for further improvement regarding the causal relationship of the structural model with job characteristics as a preceding factor. Third, contrary to expectations, the supervisor''s learning immersion leadership did not show any significant moderating effects in the relationship between the expected preceding variable and learning agility, and also between learning agility and innovative behavior. The supervisor''s learning immersion leadership means "the supervisor leading members in additional learning necessary for their jobs". Thus, instead of adhering to the outdated ways of the past, learning immersion leadership should embrace new changes by responding quickly and flexibly.