交互記憶系統（TMS）代表一種新興狀態，捕捉團隊效能所需的基本知識在團隊成員間如何組織、呈現和傳播的演變和動態認知框架。TMS涉及理解他人的記憶系統，促進跨功能的意識和團隊內“誰知道什麼”的共享理解。當團隊利用這種共享理解有效地分配任務時，交互記憶的實際意義就變得顯而易見——解決“誰將做什麼”的關鍵問題。
TMS的核心在於人際溝通——“交互”一詞表示個體間的動態溝通互動。現有的工具未能捕捉到TMS出現背後的動態和溝通過程。要掌握TMS如何在團隊內部演變和積極發展，迫切需要更真實的基於過程的衡量方法。這種衡量方法應該檢查實時互動、溝通動態和促成TMS形成及有效運作的協作過程。
將焦點從單純的輸出衡量轉向以過程為導向的評估，能夠更深入地洞察TMS如何在團隊環境中通過溝通顯現並被積極利用的機制。具體來說，這項研究深入探討了創意問題解決工作坊中團隊互動的複雜動態，旨在了解TMS如何出現、演變並隨時間在團隊間持續存在。
本研究著重分析自然發生的互動行為，通過分析互動代碼的頻率和模式。通過滯後序列分析（LSA），識別出序列編碼互動中的時間模式，揭示了TMS和基於團隊的問題解決的序列依賴性及其含義。研究發現的主要行為序列模式揭示了兩種主要的互動對話結構——中心化與社會認知結構，以及從這些結構中衍生出四種不同的互動模式：決策驅動、促進共識、發現未共享的知識和引出新提議。這些模式代表了團隊發展和維持TMS的不同動態過程。

Transactive Memory System (TMS) represents an emergent state that captures the evolving and dynamic cognitive framework within which essential knowledge for team efficacy is organized, represented, and disseminated among team members. TMS involves understanding another's memory system, fostering a cross-functional awareness and shared understanding of "who knows what" within a team. The practical implications of transactive memory become evident when teams leverage this shared understanding to allocate tasks efficiently—addressing the crucial question of "who will do what".
At the core of TMS lies interpersonal communication—the term "transactive" denotes dynamic communicative interactions between individuals. Existing instruments fall short in capturing the dynamic and communicative processes that underlie the emergence of TMS. To grasp how TMS evolves and actively develops within a team, there is a pressing need for a more authentic process-based measure. This measure should examine real-time interactions, communicative dynamics, and collaborative processes that contribute to the formation and effective functioning of TMS.
Shifting the focus from mere output measures to a process-oriented assessment allows for deeper insights into the mechanisms through which TMS communicatively emerges and is actively utilized within a team context. Specifically, this research delved into the complex dynamics of team interactions within a creative problem-solving workshop, aiming to understand how TMS emerges, evolves, and is sustained over time within and across teams.
The study focuses on dissecting naturally occurring interaction behaviors by analyzing the frequency and patterns of interaction codes. Through Lag Sequential Analysis (LSA), which identifies temporal patterns in sequentially coded interactions, the study reveals sequential dependencies and their implications for TMS and team-based problem-solving. Findings of predominant behavioral sequence patterns revealed two primary interactive conversational structures -Centralized and Social Metaknowledge, and four distinct interaction modes emerging from these structures: decision-driven, promoting shared-understanding, discovering unshared knowledge, and eliciting new proposals. These modes represent distinct dynamic processes through which teams developed and sustained TMS.

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