教材分享行為模型、誘因、防止盜版與共謀之系統設計

Abstract

在九年一貫教育體系與一綱多本政策下，近年來國內教材分享網站蓬勃發展。個人電腦普及與與同儕對同儕式網路讓老師能夠方便地在教材分享系統交流教材與教學經驗，教師可以增進教學能力並提供高品質教育以增進下一代孩童的競爭力。但是，目前缺少鼓勵分享行為的有效誘因。 本論文探討國小教師在台灣學術網路(TANet)上分享教材的問題，賴家將提出一混合式同儕對同儕式教材分享系統[Lai05]為基礎，其中教師為節點而教育局扮演超節點的角色。我們探討四個對教材分享系統成功但卻還沒被解決的重要議題：一、防止盜版(piracy)與共謀(collusion)現象。二、設計教材分享環境下的聲譽(reputation)系統以衡量個別教師的貢獻。三、教材分享系統會員數成長與教師上傳行為模式。四、評估不同獎勵政策對系統教材質與量的影響。 首先我們在同儕對同儕式教材分享系統上設計智慧財產權管理的機制，可以防止盜版的行為。藉由對稱式加密法與整合智慧財產權管理方法，沒有向教育局要求使用執照的盜版教材無法解密使用。同時，教育局會儲存所有下載的交易紀錄，以表揚教材提供者。我們提供防止盜版的環境讓教材原創者可以保護自己智慧財產權，並進而增加教師使用系統的意願。 本論文並提出合成式聲譽系統供教育局評估個別教師對教材分享社群的貢獻。此聲譽系統由教材所得平均分數、被下載次數、撰寫評論比率與上傳檔案份數所組成。教育局可以依照社群發展階段改變係數來誘導不同行為。 在教材平均分數一項中包含信任因子以計算評論的可信度。我們採用個人化相似測度(Srivatsa et al. 2005)來減輕共謀團體上傳的評分。共謀團體因為與正常老師給的評分相當不同，所以其可信度會降低。我們可藉此減輕共謀行為的影響，並提高聲譽系統的正確性。 我們建立教師加入或離開社群與上傳教材的模型，並討論這些行為之間的相互影響。根據科技接受模型(technology acceptance model)與呂慧甄對影響教師知識分享因素研究(Lu 2003)，並以S曲線建立教材分享系統行為的機率模型。此模型掌握影響教師行為的重要因子且符合基本經濟學原理，我們相信可做為未來從事實驗的理論基礎。 根據此模型，我們評估了兩種獎勵誘因政策給教材上傳者之影響，分別是相對排名法(relative ranking)與閥值法(threshold)。相對排名法可以讓高品質教材上傳者得到較多獎勵，讓他們上傳意願提高，增進教材的平均水準。而閥值法齊頭式地鼓勵教材上傳行為，可以增加上傳的數量。 在同儕對同儕式教材分享系統上我們實做智財權與共謀行為減輕的機制。許可執照管理與可信度計算功能在教育局的層次實現，而許可執照上傳、執照要求、檔案加密與智財權播放器則在教師端應用程式發展。此外，此系統也可做為未來從事相關實驗蒐集實際資料的平台。 我們在教材分享系統上設計智財權機制並在合成式聲譽系統中採用個人化相似測度以防止盜版與共謀，並開發相關實作環境供未來實驗使用。我們並建構教師在教材分享社群中的加入、離開與上傳行為的模型。根據此模型，我們設計與評估對教育管理當局重要的兩種誘因政策。本論文提出研究教材分享的理論基礎與實驗所需平台供未來研究者使用。

Teaching material sharing (TMS) websites grow rapidly in Taiwan due to one-outline-multiple-texts policy under nine-year compulsory curriculum. The prevalence of personal computers and peer-to-peer (P2P) networks provide convenient way to share teaching resources and experiences on TMS system. Teachers can enhance their teaching abilities and provide high-quality education to increase the competitiveness of our next generation. However, no effective incentives to encourage sharing activities are proposed. This thesis focuses on TMS over TANet among elementary teachers. Lai (2005) designed a hybrid P2P TMS system where teachers are peers and bureaus of education play the role of super-peer. We consider four issues that are critical to the success of TMS but not addressed in Lai’s research: (i) Reinforcement of Lai’s TMS system against piracy and collusion; (ii) Design of a reputation system to evaluate teachers’ contribution to TMS community; (iii) Behavior modeling of membership growth and TM upload; (iv) Evaluation of different reward policies which influence content quality and quantity on TMS system. We first design and add Digital Rights Management (DRM) to Lai’s system against piracy. By using symmetric encryption and integrating license management function of DRM solution, pirated files without acquiring legal licenses form bureau of education can not be decrypted for access. Also super-peers store all download transaction records for giving credits to content providers. We provide a piracy-free sharing environment for content creators to protect intellectual property rights and thus increase teacher’s willingness to share. We then proposed a synthetic reputation for bureau of education to evaluate teachers’ contribution to the TMS community. The synthetic reputation of a peer is defined as the summation of average score received from other peers, TM downloaded times, review return ratio of the peer, and number of upload TM. Bureau of education can change the coefficient of reputation formula at different stages to induce desired behaviors. The component of average score received contains credibility factor to reflect reliability of peers’ reviews. We adopted Personalized Similarity Measure (Srivatsa et al. 2005) to reduce the impact of reviews of collusive peers. Collusive peers get low credibility factor because their dishonest feedbacks are not similar to normal peers’. Thus we can alleviate review collusion to improve the accuracy of reputation system. We model teachers’ willingness to join, leave, probability to upload and define the interactions among these behaviors. We used technology acceptance model (TAM) and finding of important factors such as TM quantity and quality or reward incentive (Lu 2003) to model the S-curve shape of join and upload behavior probability distribution. This model captures essential factors and reasonable behavior pattern which obey economic principle that we believe it is suitable as theoretical model for experiment. On the basis of behavior model, we evaluate the impacts of two different reward policies, relative ranking and threshold, to allocate bonus to content creators. Under relative ranking policy, high-quality content creators with higher reputation earn more bonuses and share more contents which improve average content quality in system. Under threshold policy, teachers equally share reward and increase content quantity. We implement license management and credibility factor calculation functions for bureau of education. License upload, license request, content encryption and decryption are developed for teachers. This TMS system provides an experiment platform for further research.