The final objective of this research project is to develop a lecture archive summarization platform that can extend learners' experience by automatically estimating and providing temporal and spatial ROI (Regions of Interest) according to multimodal features and learners' learning logs in lecture archives that record face-to-face lectures. To develop this platform, we (a) establish a method for extracting spatiotemporal multimodal features of lecture archives and (b) construct a method for estimating a learning style model based on the learning logs when watching the archives with the extracted features. Furthermore, to maximize the learning effect, we will (c) develop a prototype system to adaptively control the spatiotemporal ROI at the terminal side according to the learning style model as an adaptive summarization. This article describes the concept of the proposed platform and the initial analysis of learners' learning logs.