# Using Chatbots as AI Conversational Partners in Language Learning
## 5 Results and Discussion
= 4.2); the participants indicated that Replika combined several clauses with different \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Replika**} & \multicolumn{2}{c}{**Kuki**} & \multicolumn{2}{c}{**Wysa**} \\ \hline  & **M** & **SD** & **M** & **SD** & **M** & **SD** & **M** & **SD** \\ \hline Spanish & 2.9 h. & 0.871 & 3.3 h. & 0.993 & 2.7 h. & 0.840 \\ Polish & 2.6 h. & 0.564 & 3.2 h. & 0.783 & 2.3 h. & 0.467 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Frequency of interaction (Choices: \(<\)1 h, 1–3 h, 3–5 h, 5+ h per week). \begin{table}
\begin{tabular}{l c c c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{\(n\) = 176 \(\alpha\) = 0.957} & \multicolumn{3}{c}{**Replika**} & \multicolumn{3}{c}{**Kuki**} & \multicolumn{3}{c}{**Wysa**} \\ \hline  & **Sp** & \multicolumn{3}{c}{**Pol.**} & \multicolumn{3}{c}{**Sp**} & \multicolumn{3}{c}{**Pol.**} & \multicolumn{3}{c}{**Sp**} & \multicolumn{3}{c}{**Pol.**} \\ \hline  & **M** & **SD** & **M** & **SD** & **M** & **SD** & **M** & **SD** & **M** & **SD** & **M** & **SD** \\ \hline
1. Semantic coherent behavior & 3.6 & 1.11 & 4.1 & 0.69 & 3.1 & 1.15 & 3.0 & 1.12 & 3.3 & 1.22 & 3.0 & 0.97 \\
2. Sentence length and complexity & 3.8 & 1.06 & 4.2 & 0.71 & 3.3 & 1.04 & 3.4 & 0.97 & 3.3 & 1.14 & 3.2 & 0.92 \\
3. R\&S technologies & 3.4 & 1.06 & 3.4 & 1.02 & 3.3 & 1.11 & 3.5 & 1.09 & 3.4 & 1.19 & 3.1 & 0.96 \\
4. Lexical richness & 3.9 & 1.08 & 4.3 & 0.74 & 3.2 & 1.16 & 3.3 & 1.16 & 3.5 & 1.22 & 3.2 & 1.12 \\
5. Grammatical accuracy & 3.6 & 1.22 & 4.0 & 0.98 & 2.4 & 1.10 & 2.5 & 1.19 & 2.4 & 1.05 & 2.4 & 0.88 \\
6. Error detection and correction & 2.5 & 1.15 & 2.7 & 1.14 & 3.1 & 1.07 & 2.8 & 0.88 & 3.1 & 1.11 & 2.9 & 0.75 \\
7. Natural conversational & 3.9 & 1.19 & 4.3 & 0.79 & 3.2 & 1.22 & 3.2 & 1.05 & 3.1 & 1.23 & 2.9 & 0.93 \\ interaction & 3.9 & 1.07 & 4.3 & 0.84 & 3.6 & 1.22 & 3.7 & 1.01 & 3.5 & 1.16 & 3.3 & 1.17 \\
9. Non-verbal language & 3.6 & 1.17 & 4.1 & 1.00 & 3.2 & 1.31 & 3.2 & 1.03 & 2.9 & 1.13 & 3.0 & 1.01 \\ \hline
10. Multimedia content & 3.7 & 1.18 & 4.3 & 0.87 & 3.4 & 1.19 & 3.3 & 1.17 & 3.0 & 1.18 & 3.3 & 1.17 \\
11. Design & 4.1 & 1.12 & 4.5 & 0.67 & 3.5 & 1.15 & 3.3 & 1.08 & 2.9 & 1.16 & 3.3 & 1.22 \\
12. Interface & 4.0 & 1.10 & 4.5 & 0.64 & 3.5 & 1.11 & 3.7 & 0.98 & 3.5 & 1.20 & 3.7 & 1.07 \\ \hline
13. Engagement & 3.9 & 1.16 & 4.3 & 0.81 & 3.1 & 1.24 & 3.1 & 1.15 & 3.2 & 1.28 & 3.1 & 1.10 \\
14. Enjoyment & 3.7 & 1.20 & 4.2 & 0.99 & 3.0 & 1.27 & 2.7 & 1.35 & 3.1 & 1.27 & 3.1 & 1.13 \\
15. Further interest & 3.5 & 1.29 & 3.9 & 1.13 & 2.7 & 1.24 & 2.3 & 1.32 & 2.9 & 1.41 & 2.7 & 1.18 \\ \hline Total & 3.7 & 1.14 & 4.1 & 0.87 & 3.2 & 1.17 & 3.1 & 1.10 & 3.1 & 1.20 & 3.1 & 1.04 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Results of the Chatbot–Human Interaction Satisfaction Model (CHISM). Five-point scale (1 = not satisfied at all to 5 = completely satisfied). levels of complexity in the conversation. The response interval was considered to be quite natural in both groups (#8 M Sp. = 3.9 and Pol. = 4.3). The only drawback mentioned was that Replika did not correct errors during the conversation (#6 M Sp. = 2.5 and Pol. = 2.7) as often as Kuki did (M Sp. = 3.1 and Pol. = 2.8), which could be a limitation for its use in language learning, particularly among lower-level students. This possible limitation was already indicated in previous works [45]. However, the teacher candidates were quite engaged (#13 M Sp. = 3.9 and Pol. = 4.3) and enjoyed the conversation with Replika (#14 M Sp. = 3.7 and Pol. = 4.2), which confirms previous results about EFL students' level of satisfaction with this conversational partner [46]. The other two chatbots, Kuki (M Sp. = 3.2 and Pol. = 3.1) and Wysa (M Sp. and Pol. = 3.1), reported similar overall scores, although Wysa was perceived to be more predictable due to its preset design.