器物的發展影響人們的行爲與思考方式，透過數位載具閱讀的人逐漸增加，然而其閱讀方式多為跳躍、非線性的淺閱讀。若需深度閱讀的內容，多數人還是傾向印成紙本，可見數位載具尚未滿足使用者於深度閱讀的需求。本研究目的為探討數位深度閱讀的情況下，不同閱讀輔助介面與筆記標註方式對閱讀的影響，透過介面設計，幫助閱讀專注，提高閱讀連貫性。研究分為三個階段，第一階段透過質性研究，透過便利抽樣邀請大學生及研究生共6位，進行閱讀任務，透過觀察與訪談，了解紙本閱讀與數位閱讀之異同，歸納成十個紙本與數位閱讀設計要點。第二階段透過單因子組間實驗設計進行三款現有軟體任務操作，探討數位閱讀標註軟體之功能，對照第一階段結果，了解現有軟體尚未滿足使用者需求之處。第三階段根據前兩階段之結果，設計介面原型共6款，實驗為雙因子混合設計，其中組內因子為閱讀輔助，共有無輔助、線輔助、面輔助三個層級，另一組間因子為筆記標註，共有單層、雙層兩個層級，故為3（閱讀輔助）X 2（筆記標註）雙因子混合設計。結果顯示：（1）面輔助閱讀方式能有效協助讀者專注於小範圍文字內容，因此最為受測者肯定；（2）整體統計結果表現以線輔助閱讀方式最佳，因其同時具有協助讀者專注和滿足大範圍閱讀需求之功能；（3）閱讀輔助方式應根據不同的閱讀類型作切換；（4）閱讀輔助介面能幫助使用者更專心閱讀，然而輔助方式需注意操作彈性；（5）快捷的筆記標註方式能減少使用者分心與操作次數，但應降低其學習成本。本研究之成果可應用於電腦版閱讀標註軟體，其中第一階段研究歸納的十個設計要點可作為往後閱讀標註軟體設計之參考。亦可以本研究為基礎探討閱讀線、面輔助，或筆記標註單、雙層的操作方式，使得數位深度閱讀體驗更加流暢。

The development of objects has impact on human behavior because more and more people read through digital devices nowadays. However, the reading paths of that are mostly in selective and non-linear ways. If it goes to deep reading, most readers will turn to printouts, which means that the deep reading experiences on digital devices have not meet their expectations. The aim of the research is to investigate the impact of several kinds of assisting reading interfaces and different annotation means under deep digital reading condition, to help reading focus and smooth the process through interfaces design. The research is formed by three stages. The qualitative research at the first stage randomly selected 6 undergraduate and graduate students to observe their deep reading behaviors. Ten deep digital reading design references were made through the semi-structured interviews. Later, compare three digital readers in present through single-factor experiment design to discuss the functions with the design references in previous stage, and list out the unsatisfied points of digital readers. Finally, according to the results of former stages, two factors were chosen based on the importance and form the interfaces design basis. The experiment is a 2 x 3 mixed factorial design. One within-subjects factor is reading assisting interfaces (i.e., non, linear, and frame). The other between-subjects factor is annotation means (i.e., single and double layer). The result suggested that: (1) Frame reading assisting interface helped readers focus on the texts effectively, that was the most welcomed one among participants; (2) Linear assisting interface had the best outcomes of the overall statistic data, for it possessed both selective and linear reading paths; (3) Reading assisting interfaces should be able to adjust according to variable reading types; (4) Reading assisting interfaces do help reading focus, but should concern about manipulating flexibility; (5) Rapid annotation means do reduce the manipulating steps and distraction of readers, but should lower the learning burdens. The result of the research can be implemented to desktop and PC readers, and the 10 deep digital reading references can be used when designing the application. Also, further research can be done based on reading assisting interfaces or annotation means to smoother the overall deep digital reading process.

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