This study aims to develop and validate effective design principles and guidelines based on learning analytics for online collaborative learning (OCL) in higher education. To this end, based on the Design and Development Research methodology, initial design principles and guidelines were derived by analyzing key factors related to OCL and learning analytics through a systematic review. Subsequently, a three-round Delphi study was conducted with a panel of five experts in relevant fields to validate their expert validity by ensuring CVI and IRA. As a result, a final set of 15 design principles and 43 detailed guidelines for their implementation were developed, categorized under four conceptual components. The learning analytics-based OCL design principles and guidelines developed through this study are expected to contribute to practical improvements by providing instructional designers in higher education with the theoretical foundation and methodological guidance necessary for planning and implementing effective, learner-centered OCL. Specifically, these design principles incorporate strategies that leverage learning data such as log data, interaction patterns, and learning outcomes generated during the learning process, to design personalized learning paths and provide feedback tailored to individual learners' characteristics and needs, thereby facilitating and deepening the knowledge construction process. This is anticipated to support data-informed educational decision-making for both instructors and learners, ultimately fostering the qualitative growth of OCL and contributing to it.