Exploring Text Revision with Backspace and Caret in Virtual Reality

Document Title

Exploring Text Revision with Backspace and Caret in Virtual Reality

Document Information

• Domain: Interaction design for text input and editing in virtual reality
• Keywords: text input, text editing, virtual reality, design space, caret control, keyboard input, experimental study

Research Background and Issues

• Identified Problems or Challenges:

  • Current virtual reality (VR) systems primarily focus on improving text input speed and accuracy (reducing spelling and grammatical errors), with insufficient attention to text revision efficiency.
  • In existing virtual keyboard designs, text deletion is typically limited to using the backspace key, which mainly operates on the content at the end of the input.
  • Caret control is inadequately designed in most VR text input systems, restricting users from efficiently revising text outside the end of the input.

• Significance:

  • In immersive virtual office or educational scenarios, users frequently need to handle text-related tasks (e.g., writing reports or sending emails). Merely completing text input is insufficient; text revision is essential for ensuring accuracy and clarity in communication.

• Research Motivation and Related Work:

  • Literature review reveals that while the academic community has proposed various innovative typing methods for VR text input, systematic support for text revision tasks is lacking.
  • Existing text revision tools (e.g., backspace key) lack flexibility, particularly when dealing with content far from the caret position, resulting in inefficiency.

Solution

• Proposed Approach:

  • A VR text revision design space combining backspace and caret control is proposed, categorized into four main combinations based on backspace granularity (character-level/word-level) and caret control continuity (discrete/continuous).
  • Four text revision techniques were implemented based on the design space:
    1. Character-level Backspace + Discrete Caret Control (CBs-DCc)
    2. Character-level Backspace + Continuous Caret Control (CBs-CCc)
    3. Word-level Backspace + Discrete Caret Control (WBs-DCc)
    4. Word-level Backspace + Continuous Caret Control (WBs-CCc)
  • These techniques were realized using handheld controllers and a virtual keyboard.

• Innovations:

  • Systematically proposed the concept of a design space, outlining potential implementation paths combining backspace and caret control.
  • Reintroduced caret control functionality, enabling users to flexibly and efficiently revise content at any position in the input.
  • Demonstrated that combinations based on word-level deletion and continuous control significantly enhance text revision efficiency.

• Implementation Steps:

  1. Conduct literature analysis to summarize shortcomings in current text revision methods.
  2. Propose the design space and define the functionalities of each combination.
  3. Develop the techniques using a virtual keyboard and handheld controllers.
  4. Design an experimental evaluation plan, collecting user performance data and subjective feedback.

Research Outcomes

• Specific Findings:

  • User experiments revealed that the combination of word-level deletion and continuous caret control (WBs-CCc) performed best in terms of revision efficiency and user satisfaction.
  • Among the four modes, WBs-CCc demonstrated significant advantages in reducing revision operations, decreasing operation time, and improving perceived ease of use.

• Advantages Compared to Existing Solutions:

  • Introducing caret control significantly improved operational flexibility, especially for revising targets far from the caret position.
  • Word-level backspace reduced repetitive deletion operations, enhancing revision efficiency.
  • Provided a generalized design framework to guide future development of VR text revision tools.

• Experimental or Evaluation Results:

  • Experimental Method:
    • A comparative experiment was conducted with 16 participants, requiring them to use the four techniques to revise target sentences containing errors at different positions and of varying types.
    • Metrics collected included operations per character, operation time, backspace frequency, and caret operation frequency.
  • Key Results:
    • WBs-CCc achieved the shortest average revision time (7978 ms) and the fewest operations (1.52 operations per character).
    • NASATLX tests indicated WBs-CCc had the lowest workload, highest SUS scores, and best user satisfaction.
  • User Feedback:
    • Word-level deletion reduced the burden of repetitive deletion, though users suggested adding support for an "undo" function.
    • Continuous caret control improved operational efficiency, but users recommended enhancing precision for fine-grained positioning.

• Limitations and Future Directions:

  • Limitations:
    • The study primarily focused on static text revision tasks, without adequately considering the dynamic integration of text input and revision.
    • Experimental conditions were relatively narrow, excluding the potential impact of other input devices (e.g., gestures, eye tracking).
  • Future Directions:
    • Investigate text revision and input interaction patterns during long-duration tasks.
    • Explore the applicability of other devices (e.g., stylus, joysticks) in text revision tasks.
    • Further optimize caret control precision, particularly improving the stability of continuous control operations.